SANAS/Base/AutoMeasure/Ceju.cs

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using OpenCvSharp;
using SmartCoalApplication.Base.CommTool;

namespace SmartCoalApplication.Base.AutoMeasure
{
    public class Ceju
    {
        /// <summary>
        /// 对图像进行二值化，得到产品目标区域
        /// </summary>
        /// <param name="image">单通道图像，一般是红色通道</param>
        /// <param name="imageContour">输出二值图</param>
        public void GetContour(Mat image, out Mat imageContour)
        {
            
            // 均值滤波
            Mat imageFilter = new Mat();
            Cv2.Blur(image, imageFilter, new OpenCvSharp.Size(5, 5));
            // 二值化，获得目标区域
            imageContour = imageFilter.Threshold(0, 1, ThresholdTypes.Otsu);
            //new Window("contour", WindowMode.Normal, imageContour * 255);
            // 闭运算，消除小孔
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(10, 10));// 结构元素
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Close, se);
            Mat fillContour = new Mat();
            Fill(imageContour, out fillContour, 1);
            //new Window("close", WindowMode.Normal, imageContour * 255);
            //new Window("fill", WindowMode.Normal, fillContour * 255);
            //Cv2.WaitKey();
            Mat fanse = 1 - fillContour;
            Scalar sum = fanse.Sum();
            Scalar sumBefore = imageContour.Sum();
            Scalar sumAfter = fillContour.Sum();
            int areaDifference = (int)sumAfter - (int)sumBefore;
            if ((int)sum != 0)//避免整张图全填充
            {
                if (areaDifference < 100)//避免填充区域过多
                    imageContour = fillContour;
            }

            #region[清理内存]
            //if (imageFilter != null)
            //{
            //    imageFilter.Dispose();
            //}
            //if (fillContour != null)
            //{
            //    fillContour.Dispose();
            //}
            #endregion
        }
        public void GetContourTongkongShuangceng(Mat image, out Mat imageContour)
        {
            // 均值滤波
            Mat imageFilter = new Mat();
            Cv2.Blur(image, imageFilter, new OpenCvSharp.Size(5, 5));
            // 二值化，获得目标区域
            imageContour = imageFilter.Threshold(0, 1, ThresholdTypes.Otsu);
            //new Window("contour", WindowMode.Normal, imageContour * 255);
            // 开运算，消除杂质，闭运算，消除小孔
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(10, 10));// 结构元素
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Open, se);
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Close, se);

            Mat fillContour = new Mat();
            Fill(imageContour, out fillContour, 1);
            //new Window("close", WindowMode.Normal, imageContour * 255);
            //new Window("fill", WindowMode.Normal, fillContour * 255);
            //Cv2.WaitKey();
            Mat fanse = 1 - fillContour;
            Scalar sum = fanse.Sum();
            Scalar sumBefore = imageContour.Sum();
            Scalar sumAfter = fillContour.Sum();
            int areaDifference = (int)sumAfter - (int)sumBefore;
            if ((int)sum != 0)//避免整张图全填充
            {
                if (areaDifference < 100)//避免填充区域过多
                    imageContour = fillContour;
            }
        }
        public void GetShenmangkongContour(Mat image, out Mat imageContour)
        {
            // 均值滤波
            Mat imageFilter = new Mat();
            Cv2.Blur(image, imageFilter, new OpenCvSharp.Size(5, 5));
            // 二值化，获得目标区域
            imageContour = imageFilter.Threshold(0, 1, ThresholdTypes.Otsu);
            //膨胀
            Mat seDilate = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(20, 1));
            Mat dilate = new Mat();
            Cv2.Dilate(imageContour, dilate, seDilate);
            // 闭运算，消除小孔
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(15, 15));// 结构元素
            Cv2.MorphologyEx(dilate, imageContour, MorphTypes.Close, se);
            Mat fillContour = new Mat();
            Fill(imageContour, out fillContour, 1);
            //new Window("fill", WindowMode.Normal, fillContour * 255);
            //Cv2.WaitKey();
            Mat fanse = 1 - fillContour;
            Scalar sum = fanse.Sum();
            Scalar sumBefore = imageContour.Sum();
            Scalar sumAfter = fillContour.Sum();
            int areaDifference = (int)sumAfter - (int)sumBefore;
            if ((int)sum != 0)//避免整张图全填充
            {
                if (areaDifference < 2000)//避免填充区域过多
                    imageContour = fillContour;
            }
        }
        /// <summary>
        /// 对图片进行上下裁剪，去掉空白的部分
        /// </summary>
        /// <param name="image">输入二值图像</param>
        /// <param name="y">输出去掉的上下边界</param>
        /// <param name="cropContour">输出裁剪后的图片</param>
        public void Crop(Mat image, out int[] y, out Mat cropContour, bool isCropFlag)
        {
            int range = 300;
            if (isCropFlag)
                range = 15;

            y = new int[2] { 0, 0 };
            for (int i = range; i < image.Rows; i++)
            {
                for (int j = 0; j < image.Cols; j++)
                {
                    if (image.Get<byte>(i, j) > 0)
                    {
                        y[0] = i;
                        break;
                    }
                }
                if (y[0] != 0)
                    break;
            }
            for (int i = image.Rows - range; i > range; i--)
            {
                for (int j = 0; j < image.Cols; j++)
                {
                    if (image.Get<byte>(i, j) > 0)
                    {
                        y[1] = i;
                        break;
                    }
                }
                if (y[1] != 0)
                    break;
            }
            cropContour = image[y[0], y[1], 0, image.Cols - 1];
        }
        /// <summary>
        /// 对全图片进行裁剪，去掉上下空白的地方，左右被亮光影响的地方
        /// </summary>
        /// <param name="image">原图</param>
        /// <param name="cropEdge">上下裁剪后边缘图，用作提取孔铜</param>
        /// <param name="y">裁剪的上下边界</param>
        /// <param name="b">用来裁剪槽孔区域的左右边界</param>
        public void Crop2(Mat image, out Mat cropEdge, out int[] y, out int[] b, bool isCropFlag)
        {
            //获得蓝色，绿色，红色通道图片
            Mat[] bgr = Cv2.Split(image);
            Mat imageBlue = bgr[0];
            Mat imageGreen = bgr[1];
            Mat imageRed = bgr[2];

            // 调色
            Mat imageNew = 0.9 * imageGreen + 0.1 * imageRed;
            //滤波
            Mat filter = new Mat();
            Cv2.BilateralFilter(imageNew, filter, 15, 150, 3);
            // 增强
            Mat zengqiang = new Mat();
            InputArray kernel = InputArray.Create<int>(new int[3, 3] { { 0, -1, 0 }, { -1, 5, -1 }, { 0, -1, 0 } });
            Cv2.Filter2D(filter, zengqiang, -1, kernel);
            Cv2.ConvertScaleAbs(zengqiang, zengqiang);
            //边缘检测
            Mat grad_x2 = new Mat();
            Sobel(zengqiang, out grad_x2);
            //开运算
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));// 结构元素                                                                                        
            Mat open = new Mat();
            Cv2.MorphologyEx(grad_x2, open, MorphTypes.Open, seOpen);

            ////閉運算
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));// 结构元素
            Mat close = new Mat();
            Cv2.MorphologyEx(open, close, MorphTypes.Close, se);
            Mat thresh2 = close.Threshold(0, 1, ThresholdTypes.Otsu);
            //填充
            Mat fill = new Mat();
            Fill(thresh2, out fill, 1);

            //new Window("grad", WindowMode.Normal, grad_x2.Threshold(0, 255, ThresholdTypes.Otsu));
            //new Window("open", WindowMode.Normal, open);
            //new Window("close", WindowMode.Normal, close);
            //Cv2.WaitKey();

            Ceju ceju = new Ceju();
            y = new int[2];
            ceju.Crop(fill, out y, out fill, isCropFlag);//用来计算左右裁剪边界
            //Mat edge = grad_x2.Threshold(0, 1, ThresholdTypes.Otsu);
            cropEdge = thresh2[y[0], y[1], 0, thresh2.Cols - 1];//用来计算孔铜边缘

            b = new int[4] { 0, 0, 0, 0 };
            int sum = 0;
            int range = 100;
            if (isCropFlag)
                range = 15;

            for (int j = range; j < fill.Cols - 1; j++)
            {
                for (int i = 0; i < fill.Rows - 1; i++)
                {
                    if (fill.Get<byte>(i, j) > 0)
                    {
                        b[0] = j;
                        break;
                    }
                }
                if (b[0] != 0)
                    break;
            }
            for (int j = b[0] + 100; j < fill.Cols - 1; j++)
            {
                sum = 0;
                for (int i = 0; i < fill.Rows - 1; i++)
                {
                    if (fill.Get<byte>(i, j) > 0)
                    {
                        sum = 1;
                        break;
                    }
                }
                if (sum == 0)
                {
                    b[1] = j;
                    break;
                }
            }
            if (b[1] - b[0] < 300)
            {
                b[0] = 0;
                for (int j = b[1] + 50; j < fill.Cols - 1; j++)
                {
                    for (int i = 0; i < fill.Rows - 1; i++)
                    {
                        if (fill.Get<byte>(i, j) > 0)
                        {
                            b[0] = j;
                            break;
                        }
                    }
                    if (b[0] != 0)
                        break;
                }
                for (int j = b[0] + 50; j < fill.Cols - 1; j++)
                {
                    sum = 0;
                    for (int i = 0; i < fill.Rows - 1; i++)
                    {
                        if (fill.Get<byte>(i, j) > 0)
                        {
                            sum = 1;
                            break;
                        }
                    }
                    if (sum == 0)
                    {
                        b[1] = j;
                        break;
                    }
                }
            }
            for (int j = fill.Cols - range; j > 0; j--)
            {
                for (int i = 0; i < fill.Rows - 1; i++)
                {
                    if (fill.Get<byte>(i, j) > 0)
                    {
                        b[3] = j;
                        break;
                    }
                }
                if (b[3] != 0)
                    break;
            }
            for (int j = b[3] - 100; j > 0; j--)
            {
                sum = 0;
                for (int i = 0; i < fill.Rows - 1; i++)
                {
                    if (fill.Get<byte>(i, j) > 0)
                    {
                        sum = 1;
                        break;
                    }
                }
                if (sum == 0)
                {
                    b[2] = j;
                    break;
                }
            }
            if (b[3] - b[2] < 300)
            {
                b[3] = 0;
                for (int j = b[2] - 50; j > 0; j--)
                {
                    for (int i = 0; i < fill.Rows - 1; i++)
                    {
                        if (fill.Get<byte>(i, j) > 0)
                        {
                            b[3] = j;
                            break;
                        }
                    }
                    if (b[3] != 0)
                        break;
                }
                for (int j = b[3] - 50; j > 0; j--)
                {
                    sum = 0;
                    for (int i = 0; i < fill.Rows - 1; i++)
                    {
                        if (fill.Get<byte>(i, j) > 0)
                        {
                            sum = 1;
                            break;
                        }
                    }
                    if (sum == 0)
                    {
                        b[2] = j;
                        break;
                    }
                }
            }
        }
        /// <summary>
        /// 用于四层孔径的裁剪，减小了左右裁剪的判定标准，其他同Crop2
        /// </summary>
        /// <param name="image"></param>
        /// <param name="cropEdge"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        public void CropSicengKongjing(Mat image, out Mat cropEdge, out int[] y, out int[] b, bool isCropFlag)
        {
            //获得蓝色，绿色，红色通道图片
            Mat[] bgr = Cv2.Split(image);
            Mat imageBlue = bgr[0];
            Mat imageGreen = bgr[1];
            Mat imageRed = bgr[2];

            // 调色
            Mat imageNew = 0.9 * imageGreen + 0.1 * imageRed;
            //滤波
            Mat filter = new Mat();
            Cv2.BilateralFilter(imageNew, filter, 15, 150, 3);
            // 增强
            Mat zengqiang = new Mat();
            InputArray kernel = InputArray.Create<int>(new int[3, 3] { { 0, -1, 0 }, { -1, 5, -1 }, { 0, -1, 0 } });
            Cv2.Filter2D(filter, zengqiang, -1, kernel);
            Cv2.ConvertScaleAbs(zengqiang, zengqiang);
            //边缘检测
            Mat grad_x2 = new Mat();
            Sobel(zengqiang, out grad_x2);
            //开运算
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));// 结构元素                                                                                        
            Mat open = new Mat();
            Cv2.MorphologyEx(grad_x2, open, MorphTypes.Open, seOpen);

            ////閉運算
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));// 结构元素
            Mat close = new Mat();
            Cv2.MorphologyEx(open, close, MorphTypes.Close, se);
            Mat thresh2 = close.Threshold(0, 1, ThresholdTypes.Otsu);
            //填充
            Mat fill = new Mat();
            Fill(thresh2, out fill, 1);

            Ceju ceju = new Ceju();
            y = new int[2];
            ceju.Crop(fill, out y, out fill, isCropFlag);//用来计算左右裁剪边界
            //Mat edge = grad_x2.Threshold(0, 1, ThresholdTypes.Otsu);
            cropEdge = thresh2[y[0], y[1], 0, thresh2.Cols - 1];//用来计算孔铜边缘

            b = new int[4] { 0, 0, 0, 0 };
            int sum = 0;
            int range = 100;
            if (isCropFlag)
                range = 15;
            for (int j = range; j < fill.Cols - 1; j++)
            {
                for (int i = 0; i < fill.Rows - 1; i++)
                {
                    if (fill.Get<byte>(i, j) > 0)
                    {
                        b[0] = j;
                        break;
                    }
                }
                if (b[0] != 0)
                    break;
            }
            for (int j = b[0] + 100; j < fill.Cols - 1; j++)
            {
                sum = 0;
                for (int i = 0; i < fill.Rows - 1; i++)
                {
                    if (fill.Get<byte>(i, j) > 0)
                    {
                        sum = 1;
                        break;
                    }
                }
                if (sum == 0)
                {
                    b[1] = j;
                    break;
                }
            }
            if (b[1] - b[0] < 50)
            {
                b[0] = 0;
                for (int j = b[1] + 50; j < fill.Cols - 1; j++)
                {
                    for (int i = 0; i < fill.Rows - 1; i++)
                    {
                        if (fill.Get<byte>(i, j) > 0)
                        {
                            b[0] = j;
                            break;
                        }
                    }
                    if (b[0] != 0)
                        break;
                }
                for (int j = b[0] + 50; j < fill.Cols - 1; j++)
                {
                    sum = 0;
                    for (int i = 0; i < fill.Rows - 1; i++)
                    {
                        if (fill.Get<byte>(i, j) > 0)
                        {
                            sum = 1;
                            break;
                        }
                    }
                    if (sum == 0)
                    {
                        b[1] = j;
                        break;
                    }
                }
            }
            for (int j = fill.Cols - range; j > 0; j--)
            {
                for (int i = 0; i < fill.Rows - 1; i++)
                {
                    if (fill.Get<byte>(i, j) > 0)
                    {
                        b[3] = j;
                        break;
                    }
                }
                if (b[3] != 0)
                    break;
            }
            for (int j = b[3] - 100; j > 0; j--)
            {
                sum = 0;
                for (int i = 0; i < fill.Rows - 1; i++)
                {
                    if (fill.Get<byte>(i, j) > 0)
                    {
                        sum = 1;
                        break;
                    }
                }
                if (sum == 0)
                {
                    b[2] = j;
                    break;
                }
            }
            if (b[3] - b[2] < 50)
            {
                b[3] = 0;
                for (int j = b[2] - 50; j > 0; j--)
                {
                    for (int i = 0; i < fill.Rows - 1; i++)
                    {
                        if (fill.Get<byte>(i, j) > 0)
                        {
                            b[3] = j;
                            break;
                        }
                    }
                    if (b[3] != 0)
                        break;
                }
                for (int j = b[3] - 50; j > 0; j--)
                {
                    sum = 0;
                    for (int i = 0; i < fill.Rows - 1; i++)
                    {
                        if (fill.Get<byte>(i, j) > 0)
                        {
                            sum = 1;
                            break;
                        }
                    }
                    if (sum == 0)
                    {
                        b[2] = j;
                        break;
                    }
                }
            }
        }
        /// <summary>
        /// 去掉槽孔的亮光，并裁剪
        /// </summary>
        /// <param name="cropContour">上下裁剪后的图片</param>
        /// <param name="border">输出裁剪后的边界</param>
        /// <param name="cropContour2">输出裁剪后的图片</param>
        /// <param name="direction">选择槽孔的左右位置，left/right</param>
        public void CropLight(Mat cropContour, out int border, out Mat cropContour2, string direction)
        {
            int[] b = new int[4] { 0, 0, 0, 0 };
            int sum = 0;
            border = 0;
            cropContour2 = new Mat();
            switch (direction)
            {
                case "left":
                    for (int j = 0; j < cropContour.Cols; j++)
                    {
                        for (int i = 0; i < cropContour.Rows; i++)
                        {
                            if (cropContour.Get<byte>(i, j) > 0)
                            {
                                b[0] = j;
                                break;
                            }
                        }
                        if (b[0] != 0)
                            break;
                    }
                    for (int j = b[0]; j < cropContour.Cols; j++)
                    {
                        sum = 0;
                        for (int i = 0; i < cropContour.Rows; i++)
                        {
                            sum += cropContour.Get<byte>(i, j);
                        }
                        if (sum == 0)
                        {
                            b[1] = j;
                            break;
                        }
                    }
                    for (int j = cropContour.Cols - 1; j > b[1]; j--)
                    {
                        for (int i = 0; i < cropContour.Rows; i++)
                        {
                            if (cropContour.Get<byte>(i, j) > 0)
                            {
                                b[3] = j;
                                break;
                            }
                        }
                        if (b[3] != 0)
                            break;
                    }
                    for (int j = b[3]; j > b[1]; j--)
                    {
                        sum = 0;
                        for (int i = 0; i < cropContour.Rows; i++)
                        {
                            sum += cropContour.Get<byte>(i, j);
                        }
                        if (sum == 0)
                        {
                            b[2] = j;
                            break;
                        }
                    }
                    if (b[1] - b[0] > 500)
                    {
                        if (Math.Abs(b[2] - b[1]) > 50)
                        {
                            cropContour2 = cropContour[0, cropContour.Rows - 1, b[0], b[1]];
                            border = b[0];
                        }
                        else
                            cropContour2 = cropContour[0, cropContour.Rows - 1, 0, cropContour.Cols - 1];
                    }
                    else
                    {
                        cropContour2 = cropContour[0, cropContour.Rows - 1, 0, b[3]];
                        border = 0;
                    }
                    break;

                case "right":
                    for (int j = cropContour.Cols - 1; j > 0; j--)
                    {
                        for (int i = 0; i < cropContour.Rows; i++)
                        {
                            if (cropContour.Get<byte>(i, j) > 0)
                            {
                                b[3] = j;
                                break;
                            }
                        }
                        if (b[3] != 0)
                            break;
                    }
                    for (int j = b[3]; j > 0; j--)
                    {
                        sum = 0;
                        for (int i = 0; i < cropContour.Rows; i++)
                        {
                            sum += cropContour.Get<byte>(i, j);
                        }
                        if (sum == 0)
                        {
                            b[2] = j;
                            break;
                        }
                    }
                    for (int j = 0; j < b[2]; j++)
                    {
                        for (int i = 0; i < cropContour.Rows; i++)
                        {
                            if (cropContour.Get<byte>(i, j) > 0)
                            {
                                b[0] = j;
                                break;
                            }
                        }
                        if (b[0] != 0)
                            break;
                    }
                    for (int j = b[0]; j < b[2]; j++)
                    {
                        sum = 0;
                        for (int i = 0; i < cropContour.Rows; i++)
                        {
                            sum += cropContour.Get<byte>(i, j);
                        }
                        if (sum == 0)
                        {
                            b[1] = j;
                            break;
                        }
                    }
                    if (b[3] - b[2] > 500)
                    {
                        if (Math.Abs(b[2] - b[1]) > 50)
                        {
                            cropContour2 = cropContour[0, cropContour.Rows - 1, b[2], cropContour.Cols - 1];
                            border = b[2];
                        }
                        else
                            cropContour2 = cropContour[0, cropContour.Rows - 1, 0, cropContour.Cols - 1];
                    }
                    else
                    {
                        cropContour2 = cropContour[0, cropContour.Rows - 1, b[0], cropContour.Cols - 1];
                        border = b[0];
                    }
                    break;
                default:
                    break;
            }
        }
        /// <summary>
        /// 针对双层深盲孔进行裁剪，上面空白区域较小，因此从第0行开始
        /// </summary>
        /// <param name="image"></param>
        /// <param name="y"></param>
        /// <param name="cropContour"></param>
        public void CropShenmangkongShuangceng(Mat image, out int[] y, out Mat cropContour, bool isCropFlag)
        {
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
            Cv2.MorphologyEx(image, image, MorphTypes.Open, se);
            int range = 200;
            if (isCropFlag)
                range = 15;

            y = new int[2] { 0, 0 };
            for (int i = 0; i < image.Rows; i++)
            {
                for (int j = range; j < image.Cols - range; j++)
                {
                    if (image.Get<byte>(i, j) > 0)
                    {
                        y[0] = i - 10;
                        break;
                    }
                }
                if (y[0] != 0)
                    break;
            }
            for (int i = image.Rows - 1; i > y[0]; i--)
            {
                for (int j = range; j < image.Cols - range; j++)
                {
                    if (image.Get<byte>(i, j) > 0)
                    {
                        y[1] = i + 10;
                        break;
                    }
                }
                if (y[1] != 0)
                    break;
            }
            cropContour = image[y[0], y[1], 0, image.Cols - 1];
        }
        /// <summary>
        /// 圖片旋轉之後出現白邊，去掉白邊
        /// </summary>
        /// <param name="image"></param>
        /// <param name="crop"></param>
        /// <param name="border"></param>
        public void CropBothSide(Mat image, out Mat crop, out int range)
        {
            range = 50;
            crop = image[range, image.Rows - range, range, image.Cols - range].Clone();

        }
        //public void CropLight2(Mat image, out int border, out Mat cropImage, string direction)
        //{
        //    Mat filter = new Mat();
        //    Cv2.BilateralFilter(image, filter, 15, 150, 3);
        //    // 增强
        //    Mat zengqiang = new Mat();
        //    InputArray kernel = InputArray.Create<int>(new int[3, 3] { { 0, -1, 0 }, { -1, 5, -1 }, { 0, -1, 0 } });
        //    Cv2.Filter2D(filter, zengqiang, -1, kernel);
        //    Cv2.ConvertScaleAbs(zengqiang, zengqiang);
        //    //边缘检测
        //    Mat grad_x = new Mat();
        //    Mat grad_x2 = new Mat();
        //    //Cv2.Sobel(zengqiang, grad_x, MatType.CV_16S, 1, 0);
        //    //Cv2.ConvertScaleAbs(grad_x, grad_x2);
        //    CejuFunction.Sobel(zengqiang, out grad_x2);
        //    ////腐蚀
        //    //Mat  se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(1, 5));
        //    //Mat erode = new Mat();
        //    //Cv2.Erode(grad_x2, erode, se);
        //    //开运算
        //    Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));// 结构元素                                                                                        
        //    Mat open = new Mat();
        //    //Cv2.MorphologyEx(close, openAfterClose,MorphTypes.Open, seOpen);
        //    Cv2.MorphologyEx(grad_x2, open, MorphTypes.Open, seOpen);

        //    ////閉運算
        //    Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));// 结构元素
        //    Mat close = new Mat();
        //    Cv2.MorphologyEx(open, close, MorphTypes.Close, se);
        //    Mat thresh2 = close.Threshold(0, 1, ThresholdTypes.Otsu);
        //    //填充
        //    Mat fill = new Mat();
        //    CejuFunction.Fill(thresh2, out fill, 1);

        //    int[] b = new int[4] { 0, 0, 0, 0 };
        //    int sum = 0;
        //    border = 0;
        //    cropImage = new Mat();
        //    switch (direction)
        //    {
        //        case "left":
        //            for (int j = 0; j < fill.Cols; j++)
        //            {
        //                for (int i = 0; i < fill.Rows; i++)
        //                {
        //                    if (fill.Get<byte>(i, j) > 0)
        //                    {
        //                        b[0] = j;
        //                        break;
        //                    }
        //                }
        //                if (b[0] != 0)
        //                    break;
        //            }
        //            for (int j = b[0]; j < fill.Cols; j++)
        //            {
        //                sum = 0;
        //                for (int i = 0; i < fill.Rows; i++)
        //                {
        //                    sum += fill.Get<byte>(i, j);
        //                }
        //                if (sum == 0)
        //                {
        //                    b[1] = j;
        //                    break;
        //                }
        //            }
        //            for (int j = fill.Cols - 1; j > b[1]; j--)
        //            {
        //                for (int i = 0; i < fill.Rows; i++)
        //                {
        //                    if (fill.Get<byte>(i, j) > 0)
        //                    {
        //                        b[3] = j;
        //                        break;
        //                    }
        //                }
        //                if (b[3] != 0)
        //                    break;
        //            }
        //            for (int j = b[3]; j > b[1]; j--)
        //            {
        //                sum = 0;
        //                for (int i = 0; i < fill.Rows; i++)
        //                {
        //                    sum += fill.Get<byte>(i, j);
        //                }
        //                if (sum == 0)
        //                {
        //                    b[2] = j;
        //                    break;
        //                }
        //            }
        //            if (b[1] - b[0] > 500)
        //            {
        //                if (Math.Abs(b[2] - b[1]) > 50)
        //                {
        //                    cropImage = fill[0, fill.Rows - 1, b[0], b[1]];
        //                    border = b[0];
        //                }
        //                else
        //                    cropImage = fill[0, fill.Rows - 1, 0, fill.Cols - 1];
        //            }
        //            else
        //            {
        //                cropImage = fill[0, fill.Rows - 1, 0, b[3]];
        //                border = 0;
        //            }
        //            break;

        //        case "right":
        //            for (int j = fill.Cols - 1; j > 0; j--)
        //            {
        //                for (int i = 0; i < fill.Rows; i++)
        //                {
        //                    if (fill.Get<byte>(i, j) > 0)
        //                    {
        //                        b[3] = j;
        //                        break;
        //                    }
        //                }
        //                if (b[3] != 0)
        //                    break;
        //            }
        //            for (int j = b[3]; j > 0; j--)
        //            {
        //                sum = 0;
        //                for (int i = 0; i < fill.Rows; i++)
        //                {
        //                    sum += fill.Get<byte>(i, j);
        //                }
        //                if (sum == 0)
        //                {
        //                    b[2] = j;
        //                    break;
        //                }
        //            }
        //            for (int j = 0; j < b[2]; j++)
        //            {
        //                for (int i = 0; i < fill.Rows; i++)
        //                {
        //                    if (fill.Get<byte>(i, j) > 0)
        //                    {
        //                        b[0] = j;
        //                        break;
        //                    }
        //                }
        //                if (b[0] != 0)
        //                    break;
        //            }
        //            for (int j = b[0]; j < b[2]; j++)
        //            {
        //                sum = 0;
        //                for (int i = 0; i < fill.Rows; i++)
        //                {
        //                    sum += fill.Get<byte>(i, j);
        //                }
        //                if (sum == 0)
        //                {
        //                    b[1] = j;
        //                    break;
        //                }
        //            }
        //            if (b[3] - b[2] > 500)
        //            {
        //                if (Math.Abs(b[2] - b[1]) > 50)
        //                {
        //                    cropImage = fill[0, fill.Rows - 1, b[2], fill.Cols - 1];
        //                    border = b[2];
        //                }
        //                else
        //                    cropImage = fill[0, fill.Rows - 1, 0, fill.Cols - 1];
        //            }
        //            else
        //            {
        //                cropImage = fill[0, fill.Rows - 1, b[0], fill.Cols - 1];
        //                border = b[0];
        //            }
        //            break;
        //        default:
        //            break;
        //    }
        //}
        /// <summary>
        /// 提取数据的提取区域
        /// </summary>
        /// <param name="cropContour2">输入去掉亮光后的图片</param>
        /// <param name="dataArea">输出提取区域dataArea[0]左，dataArea[1]右</param>
        /// /// <param name="direction">槽孔的位置方向，left/right</param>
        public void GetDataArea(Mat cropContour2, out int[] dataArea, string direction)
        {
            int[] rowSum = new int[cropContour2.Rows];
            int max = 0;
            int fillBorder = 0;
            for (int i = 0; i < cropContour2.Rows; i++)
            {
                for (int j = 0; j < cropContour2.Cols; j++)
                    rowSum[i] += cropContour2.Get<byte>(i, j);
            }
            max = rowSum.Max();
            for (int i = 0; i < rowSum.Length; i++)
            {
                if (rowSum[i] > max - 50)
                {
                    fillBorder = i;
                    break;
                }
            }
            Mat fill = cropContour2.Clone();
            Cv2.Rectangle(fill, new Rect(0, fillBorder, cropContour2.Cols, cropContour2.Rows - fillBorder), new Scalar(1), -1);
            //提取區域
            dataArea = new int[2] { 0, 0 };
            int[] colSum = new int[fill.Cols];
            for (int j = 100; j < fill.Cols - 100; j++)
            {
                for (int i = 0; i < fill.Rows; i++)
                {
                    colSum[j] += fill.Get<byte>(i, j);
                }
            }
            max = colSum.Max();
            switch (direction)
            {
                case "right":
                    //for (int j = 0; j < colSum.Length; j++)
                    //{
                    //    if (colSum[j] > max - 10)
                    //    {
                    //        dataArea[0] = j+100;
                    //        break;
                    //    }
                    //}
                    dataArea[0] = 100;
                    for (int j = dataArea[0] + 100; j < colSum.Length - 100; j++)
                    {
                        if (colSum[j] > max - 10)
                        {
                            dataArea[1] = j;
                            break;
                        }
                    }
                    if (dataArea[1] == 0)
                        dataArea[1] = dataArea[0] + 100;
                    //dataArea[0] = 100;
                    if (dataArea[1] - dataArea[0] > 200)
                        dataArea[1] = dataArea[0] + 200;
                    break;
                case "left":
                    //for (int j = colSum.Length - 1; j > 0; j--)
                    //{
                    //    if (colSum[j] > max - 10)
                    //    {
                    //        dataArea[1] = j+100;
                    //        break;
                    //    }
                    //}
                    dataArea[1] = cropContour2.Cols - 100;
                    for (int j = dataArea[1] - 100; j > 100; j--)
                    {
                        if (colSum[j] > max - 10)
                        {
                            dataArea[0] = j;
                            break;
                        }
                    }
                    if (dataArea[0] == 0)
                        dataArea[0] = dataArea[1] - 100;
                    //dataArea[1] = cropContour2.Cols - 100;
                    if (dataArea[1] - dataArea[0] > 200)
                        dataArea[0] = dataArea[1] - 200;
                    break;
            }
        }

        /// <summary>
        /// 得到浅盲孔的数据提取区域
        /// </summary>
        /// <param name="cropContour">裁剪后的二值图像</param>
        /// <param name="dataArea">输出提取区域，从左至右分别是[0][1][2][3]</param>
        public void GetMangkongDataAreaForQian(Mat cropContour, out int[] dataArea)
        {
            dataArea = new int[4];
            int[] middleArea = new int[2];
            int[] sum = new int[cropContour.Cols];
            //每列求和
            for (int j = 0; j < cropContour.Cols; j++)
            {
                sum[j] = 0;
                for (int i = 0; i < cropContour.Rows; i++)
                {
                    sum[j] += cropContour.Get<byte>(i, j);
                }
            }
            //求中部区域
            int max = sum.Max();
            for (int j = 0; j < sum.Length; j++)
            {
                if (sum[j] > max - 10)
                {
                    middleArea[0] = j;
                    break;
                }
            }
            for (int j = sum.Length - 1; j > 0; j--)
            {
                if (sum[j] > max - 10)
                {
                    middleArea[1] = j;
                    break;
                }
            }

            //第一次容错
            if(middleArea[1]- middleArea[0] < 100)
            {
                for (int j = 0; j < sum.Length; j++)
                {
                    if (sum[j] > max - 20)
                    {
                        middleArea[0] = j;
                        break;
                    }
                }
                for (int j = sum.Length - 1; j > 0; j--)
                {
                    if (sum[j] > max - 20)
                    {
                        middleArea[1] = j;
                        break;
                    }
                }
            }

            //每行求和
            int[] rowsSum = new int[cropContour.Rows];
            for (int i = 0; i < cropContour.Rows; i++)
            {
                rowsSum[i] = 0;
                for (int j = 0; j < cropContour.Cols; j++)
                {
                    rowsSum[i] += cropContour.Get<byte>(i, j);
                }
            }
            //得到填充上界,其下填为0
            max = rowsSum.Max();
            int fillBorder = new int();
            for (int i = 0; i < rowsSum.Length; i++)
            {
                if (rowsSum[i] > max / 2)
                {
                    fillBorder = i;
                    break;
                }
            }
            Mat fill = cropContour.Clone();
            Cv2.Rectangle(fill, new Rect(0, fillBorder, cropContour.Cols, cropContour.Rows - fillBorder), new Scalar(1), -1);
            //每列求和
            int[] colSum = new int[fill.Cols];
            for (int j = 0; j < fill.Cols; j++)
            {
                colSum[j] = 0;
                for (int i = 0; i < fill.Rows; i++)
                {
                    colSum[j] += fill.Get<byte>(i, j);
                }
            }
            //左，右最大值
            int[] left = colSum.Skip(middleArea[0] - 500).Take(500).ToArray();
            int[] right = colSum.Skip(middleArea[1]).Take(500).ToArray();
            int leftMax = left.Max();
            int rightMax = right.Max();
            //数据提取区域
            int range = 100;
            if (colSum[middleArea[0] - 100] < leftMax - 10 || colSum[middleArea[1] + 100] < rightMax - 10)
                range = 0;
            for (int j = middleArea[0] - range; j > middleArea[0] - 500 && j > 0; j--)
            {
                if (colSum[j] > leftMax - 10)
                {
                    dataArea[1] = j;
                    break;
                }
            }
            if (dataArea[1] == 0) dataArea[1] = leftMax;
            for (int j = dataArea[1] - 100; j < dataArea[1]; j++)
            {
                if (colSum[j] > leftMax - 10)
                {
                    dataArea[0] = j;
                    break;
                }
            }
            for (int j = middleArea[1] + range; j < middleArea[1] + 500; j++)
            {
                if (colSum[j] > rightMax - 5)
                {
                    dataArea[2] = j;
                    break;
                }
            }
            for (int j = dataArea[2] + 100; j > dataArea[2]; j--)
            {
                if (colSum[j] > rightMax - 5)
                {
                    dataArea[3] = j;
                    break;
                }
            }
            if (dataArea[1] == 0)
            {
                dataArea[1] = middleArea[0] - 70;//不加100是因为出去还要加20
                dataArea[0] = dataArea[1] - 100;
            }
            if (dataArea[0] == 0)
            {
                dataArea[0] = dataArea[1] - 100;
                if (colSum[dataArea[0]] < leftMax - 10)
                    dataArea[0] = dataArea[1] - 30;
            }

            if (dataArea[2] == 0)
            {
                dataArea[2] = middleArea[1] + 70;//不加100是因为出去还要加20
                dataArea[3] = dataArea[2] + 100;
            }
            if (dataArea[3] == 0)
            {
                dataArea[3] = dataArea[2] + 100;
                if (colSum[dataArea[3]] < rightMax - 10)//防止加完出界
                    dataArea[3] = dataArea[2] + 30;
            }
            if (dataArea[1] - dataArea[0] < 50)
                dataArea[1] += 50;
            if (dataArea[3] - dataArea[2] < 50)
                dataArea[2] -= 50;
        }
        /// <summary>
        /// 得到浅盲孔的数据提取区域
        /// </summary>
        /// <param name="cropContour">裁剪后的二值图像</param>
        /// <param name="dataArea">输出提取区域，从左至右分别是[0][1][2][3]</param>
        public void GetMangkongDataArea(Mat cropContour, out int[] dataArea)
        {
            dataArea = new int[4];
            int[] middleArea = new int[2];
            int[] sum = new int[cropContour.Cols];
            //每列求和
            for (int j = 0; j < cropContour.Cols; j++)
            {
                sum[j] = 0;
                for (int i = 0; i < cropContour.Rows; i++)
                {
                    sum[j] += cropContour.Get<byte>(i, j);
                }
            }
            
            //求中部区域
            int max = sum.Max();
            for (int j = 0; j < sum.Length; j++)
            {
                if (sum[j] > max - 20)
                {
                    middleArea[0] = j;
                    break;
                }
            }
            for (int j = sum.Length - 1; j > 0; j--)
            {
                if (sum[j] > max - 20)
                {
                    middleArea[1] = j;
                    break;
                }
            }

            //第一次容错
            if (middleArea[1] - middleArea[0] < 110)
            {
                for (int j = 0; j < sum.Length; j++)
                {
                    if (sum[j] > max - 80)
                    {
                        middleArea[0] = j;
                        break;
                    }
                }
                for (int j = sum.Length - 1; j > 0; j--)
                {
                    if (sum[j] > max - 80)
                    {
                        middleArea[1] = j;
                        break;
                    }
                }
            }

            //每行求和
            int[] rowsSum = new int[cropContour.Rows];
            for (int i = 0; i < cropContour.Rows; i++)
            {
                rowsSum[i] = 0;
                for (int j = 0; j < cropContour.Cols; j++)
                {
                    rowsSum[i] += cropContour.Get<byte>(i, j);
                }
            }
            //得到填充上界,其下填为0
            max = rowsSum.Max();
            int fillBorder = new int();
            for (int i = 0; i < rowsSum.Length; i++)
            {
                if (rowsSum[i] > max / 2)
                {
                    fillBorder = i;
                    break;
                }
            }
            Mat fill = cropContour.Clone();
            Cv2.Rectangle(fill, new Rect(0, fillBorder, cropContour.Cols, cropContour.Rows - fillBorder), new Scalar(1), -1);
            //每列求和
            int[] colSum = new int[fill.Cols];
            for (int j = 0; j < fill.Cols; j++)
            {
                colSum[j] = 0;
                for (int i = 0; i < fill.Rows; i++)
                {
                    colSum[j] += fill.Get<byte>(i, j);
                }
            }
            //左，右最大值
            int[] left = colSum.Skip(middleArea[0] - 500).Take(500).ToArray();
            int[] right = colSum.Skip(middleArea[1]).Take(500).ToArray();
            int leftMax = left.Max();
            int rightMax = right.Max();
            //数据提取区域
            int range = 100;
            if (colSum[middleArea[0] - 100] < leftMax - 10 || colSum[middleArea[1] + 100] < rightMax - 10)
                range = 0;
            for (int j = middleArea[0] - range; j > middleArea[0] - 500 && j > 0; j--)
            {
                if (colSum[j] > leftMax - 10)
                {
                    dataArea[1] = j;
                    break;
                }
            }
            for (int j = dataArea[1] - 100; j < dataArea[1]; j++)
            {
                if (colSum[j] > leftMax - 10)
                {
                    dataArea[0] = j;
                    break;
                }
            }
            for (int j = middleArea[1] + range; j < middleArea[1] + 500; j++)
            {
                if (colSum[j] > rightMax - 5)
                {
                    dataArea[2] = j;
                    break;
                }
            }
            for (int j = dataArea[2] + 100; j > dataArea[2]; j--)
            {
                if (colSum[j] > rightMax - 5)
                {
                    dataArea[3] = j;
                    break;
                }
            }
            if (dataArea[1] == 0)
            {
                dataArea[1] = middleArea[0] - 70;//不加100是因为出去还要加20
                dataArea[0] = dataArea[1] - 100;
            }
            if (dataArea[0] == 0)
            {
                dataArea[0] = dataArea[1] - 100;
                if (colSum[dataArea[0]] < leftMax - 10)
                    dataArea[0] = dataArea[1] - 30;
            }

            if (dataArea[2] == 0)
            {
                dataArea[2] = middleArea[1] + 70;//不加100是因为出去还要加20
                dataArea[3] = dataArea[2] + 100;
            }
            if (dataArea[3] == 0)
            {
                dataArea[3] = dataArea[2] + 100;
                if (colSum[dataArea[3]] < rightMax - 10)//防止加完出界
                    dataArea[3] = dataArea[2] + 30;
            }
            if (dataArea[1] - dataArea[0] < 50)
                dataArea[1] += 50;
            if (dataArea[3] - dataArea[2] < 50)
                dataArea[2] -= 50;
        }
        /// <summary>
        /// 提取第一條橫綫縱坐標
        /// </summary>
        /// <param name="image">輸入二值化圖像</param>
        /// <param name="averageCoordinateNew">輸出坐標</param>
        /// <param name="leftBorder">左邊界</param>
        /// <param name="rightBorder">右边界</param>
        /// <param name="direction">大于等于0时，记录大于0的点，小于0记录等于零的点</param>
        public void ExtractLines(Mat image, out double averageCoordinateNew, int leftBorder, int rightBorder, int direction)
        {
            //数组长宽
            int rows = image.Rows;
            int cols = image.Cols;
            int count = 0;
            int sum = 0;

            // 对循环次数计数，防止程序卡死
            int circleCount = 0;

            //当点的个数少于5的时候循环
            while (count < 5)
            {
                count = 0;
                sum = 0;
                //每次循环，寻找范围向下移动5个像素

                //遍历，寻找线条上的点，并记录纵坐标
                for (int j = leftBorder; j < rightBorder; j++)
                {
                    for (int i = 0; i < rows; i++)
                    {
                        if (direction >= 0)
                        {
                            if (image.Get<byte>(i, j) > 0)
                            {
                                sum += i;
                                count++;
                                break;
                            }
                        }
                        else
                        {
                            if (image.Get<byte>(i, j) == 0)
                            {
                                sum += i;
                                count++;
                                break;
                            }
                        }
                    }
                }

                // 超过30次跳出
                if(circleCount <= 30)
                {
                    circleCount++;
                }
                else
                {
                    break;
                }
            }
            averageCoordinateNew = sum / count;
        }
        /// <summary>
        /// 提取非第一条横线纵坐标
        /// </summary>
        /// <param name="image">输入二值化图像</param>
        /// <param name="averageCoordinateNew">输出纵坐标</param>
        /// <param name="leftBorder">左边界</param>
        /// <param name="rightBorder">右边界</param>
        /// <param name="averageCoordinate">上一条线的坐标</param>
        /// <param name="direction">大于等于0时，记录大于0的点，小于0时记录等于零的点</param>
        public void ExtractLines(Mat image, out double averageCoordinateNew, int leftBorder, int rightBorder, double averageCoordinate, int direction)
        {
            //ImageShow(image*255);
            //数组长宽
            int rows = image.Rows;
            int cols = image.Cols;
            int count = 0;
            int sum = 0;
            int upperBound = (int)averageCoordinate + 15;
            int lowerBound = (int)averageCoordinate + 45;

            //当点的个数少于5的时候循环
            while (count < 5)
            {
                count = 0;
                sum = 0;
                //每次循环，寻找范围向下移动5个像素
                upperBound = upperBound + 5;
                lowerBound = lowerBound + 5;
                if (lowerBound > image.Rows)
                    break;
                //遍历，寻找线条上的点，并记录纵坐标
                int value = 0;
                for (int j = leftBorder; j < rightBorder; j++)
                {
                    for (int i = upperBound; i < lowerBound; i++)
                    {
                        if (direction >= 0)
                        {
                            value = image.Get<byte>(i, j);
                            if (value > 0)
                            {
                                sum += i;
                                count++;
                                break;
                            }
                        }
                        else
                        {
                            if (image.Get<byte>(i, j) == 0)
                            {
                                sum += i;
                                count++;
                                break;
                            }
                        }
                    }
                }


            }
            averageCoordinateNew = count == 0 ? 0 : sum / count;
        }
        /// <summary>
        /// 从下向上提取第一条横线纵坐标
        /// </summary>
        /// <param name="image">輸入二值化圖像</param>
        /// <param name="averageCoordinateNew">輸出坐標</param>
        /// <param name="leftBorder">左邊界</param>
        /// <param name="rightBorder">右边界</param>
        /// <param name="direction">大于等于0时，记录大于0的点，小于0记录等于零的点</param>
        public void ExtractLines2(Mat image, out double averageCoordinateNew, int leftBorder, int rightBorder, int direction)
        {
            //数组长宽
            int rows = image.Rows;
            int cols = image.Cols;
            int count = 0;
            int sum = 0;
            int tag = 0;
            //当点的个数少于5的时候循环
            while (count < 5)
            {
                count = 0;
                sum = 0;
                //每次循环，寻找范围向下移动5个像素

                //遍历，寻找线条上的点，并记录纵坐标
                for (int j = leftBorder; j < rightBorder; j++)
                {
                    for (int i = rows - 1; i > 0; i--)
                    {
                        if (i == 1)
                            tag += 1;
                        if (direction >= 0)
                        {
                            if (image.Get<byte>(i, j) > 0)
                            {
                                sum += i;
                                count++;
                                break;
                            }
                        }
                        else
                        {
                            if (image.Get<byte>(i, j) == 0)
                            {
                                sum += i;
                                count++;
                                break;
                            }
                        }
                    }
                    if (tag == 3)
                        break;
                }
                if (tag == 3)
                    break;


            }
            averageCoordinateNew = (count == 0) ? 0 : sum / count;
        }
        /// <summary>
        /// 从下向上提取横线纵坐标
        /// </summary>
        /// <param name="image">输入二值化图像</param>
        /// <param name="averageCoordinateNew">输出纵坐标</param>
        /// <param name="leftBorder">左边界</param>
        /// <param name="rightBorder">右边界</param>
        /// <param name="averageCoordinate">上一条线的坐标</param>
        /// <param name="direction">大于等于0时，记录大于0的点，小于0时记录等于零的点</param>
        public void ExtractLines2(Mat image, out double averageCoordinateNew, int leftBorder, int rightBorder, double averageCoordinate, int direction)
        {
            //数组长宽
            int rows = image.Rows;
            int cols = image.Cols;
            int sum = 0, count = 0;
            //遍历范围的上界和下界
            int upperBound = (int)averageCoordinate - 45;
            int lowerBound = (int)averageCoordinate - 10;

            //当点的个数少于5的时候循环
            while (count < 5)
            {
                count = 0;
                sum = 0;
                //每次循环，寻找范围向下移动5个像素
                upperBound = upperBound - 5;
                lowerBound = lowerBound - 5;
                if (upperBound < 0)
                    break;
                //遍历，寻找线条上的点，并记录纵坐标
                for (int j = leftBorder; j < rightBorder; j++)
                {
                    for (int i = lowerBound; i > upperBound; i--)
                    {
                        if (direction >= 0)
                        {
                            if (image.Get<byte>(i, j) > 0)
                            {
                                sum += i;
                                count++;
                                break;
                            }
                        }
                        else
                        {
                            if (image.Get<byte>(i, j) == 0)
                            {
                                sum += i;
                                count++;
                                break;
                            }
                        }
                    }
                }
            }
            averageCoordinateNew = count==0 ? 0 : sum / count;
        }
        /// <summary>
        /// 提取第一条竖线的横坐标，从左往右
        /// </summary>
        /// <param name="image">输入二值图像</param>
        /// <param name="result">输出坐标结果</param>
        /// <param name="upperBound">上边界</param>
        /// <param name="lowerBound">下边界</param>
        public void ExtractVerticalLinesL2R(Mat image, out double result, int upperBound, int lowerBound, int showMat = 0)
        {
            int rows = image.Rows;
            int cols = image.Cols;
            List<int> sum = new List<int>();
            int k = 0;
            while (sum.Count == 0)
            {
                if (upperBound - 5 * k < 0 || lowerBound + 5 * k > image.Rows) break;
                //解决两层板有些孔铜找不到的问题
                for (int i = upperBound - 5 * k; i < lowerBound + 5 * k; i++)
                {
                    for (int j = 0; j < cols; j++)
                    {
                        if (image.Get<byte>(i, j) > 0)
                        {
                            sum.Add(j);
                            break;
                        }
                    }
                }
                ++k;
            }
            ////int count = 0;
            //for (int i = upperBound; i < lowerBound; i++)
            //{
            //    for (int j = 0; j < cols; j++)
            //    {
            //        if (image.Get<byte>(i, j) > 0)
            //        {
            //            sum.Add(j);
            //            //sum += j;
            //            //count++;
            //            break;
            //        }
            //    }
            //}
            //if (sum.Count == 0)
            //    result = 1;// 0;
            //else
            result = sum.Average();// / count;
            //if (showMat > 0)
            //{
            //    Mat imageClone = image.Clone() * 127;
            //    Cv2.Line(imageClone, 0, upperBound, cols - 1, upperBound, new Scalar(255));
            //    Cv2.Line(imageClone, 0, lowerBound, cols - 1, lowerBound, new Scalar(255));
            //    Cv2.ImWrite(@"C:\Users\54434\Desktop\imageClone_" + showMat + ".png", imageClone);
            //}
            //////对自动结果不正确（这里使用距离过远来判定）的扩展运算
            ////double result1 = 0;
            if (showMat > 0 && result > 20/*countV > (upperBound + lowerBound) / 2*/)
            {
                sum.Clear();
                //sum = 0;
                //count = 0;
                ////Mat imageClone = image.Clone() * 127;
                ////Cv2.Line(imageClone, 0, upperBound, cols - 1, upperBound, new Scalar(255));
                ////Cv2.Line(imageClone, 0, lowerBound, cols - 1, lowerBound, new Scalar(255));
                ////Cv2.ImWrite(@"C:\Users\54434\Desktop\imageClone_" + showMat + ".png", imageClone);
                //////int sum = 0;
                //////int count = 0;
                bool sumAdd = false;

                for (int i = upperBound - 5; i < lowerBound + 5; i++)
                {
                    sumAdd = false;
                    for (int j = 0; j < 20; j++)
                    {
                        if (image.Get<byte>(i, j) > 0)
                        {
                            sumAdd = true;
                            sum.Add(j);
                            //sum += j;
                            //count++;
                            break;
                        }
                    }
                    if (!sumAdd && sum.Count > 0)
                        break;
                }

                if (sum.Count == 0)
                {
                    for (int i = upperBound - 5; i < lowerBound + 5; i++)
                    {
                        sumAdd = false;
                        for (int j = 0; j < 26; j++)
                        {
                            if (image.Get<byte>(i, j) > 0)
                            {
                                sumAdd = true;
                                sum.Add(j);
                                //sum += j;
                                //count++;
                                break;
                            }
                        }
                        if (!sumAdd && sum.Count > 0)
                            break;
                    }

                    //for (int i = upperBound - 5; i < lowerBound + 5; i++)
                    //{
                    //    sumAdd = false;
                    //    for (int j = cols - 1; j > cols - 26; j--)
                    //    {
                    //        if (image.Get<byte>(i, j) > 0)
                    //        {
                    //            sumAdd = true;
                    //            sum += j;
                    //            count++;
                    //            break;
                    //        }
                    //    }
                    //    if (!sumAdd && sum > 0)
                    //        break;
                    //}
                }

                // 输出平均横坐标
                if (sum.Count > 0)
                    result = sum.Average();// / count;
            }
            else if (showMat > 0)
            {//对自动结果不正确（这里使用垂直方向不整齐来判定）的扩展运算
                sum.Sort();
                for (int i = 0; i < sum.Count - 1; i++)
                {
                    if (sum[i + 1] - sum[i] > 10)
                    {
                        for (int j = sum.Count - 1; j > i; j--)
                            sum.RemoveAt(j);
                        break;
                    }
                }
                // 输出平均横坐标
                if (sum.Count > 0)
                    result = sum.Average();// / count;
                //Mat imageClone = image.Clone() * 127;
                //Cv2.Line(imageClone, 0, upperBound, cols - 1, upperBound, new Scalar(255));
                //Cv2.Line(imageClone, 0, lowerBound, cols - 1, lowerBound, new Scalar(255));
                //Cv2.ImWrite(@"C:\Users\54434\Desktop\imageClone_" + showMat + ".png", imageClone);
            }
            ////对自动结果不正确（这里使用距离过远来判定）的扩展运算
            //double result1 = 0;

            //// 输出平均横坐标
            //result = sum / count;
        }
        /// <summary>
        /// 提取第二条竖线的横坐标，从左往右
        /// </summary>
        /// <param name="image">输入二值图像</param>
        /// <param name="result">输出坐标结果</param>
        /// <param name="upperBound">上边界</param>
        /// <param name="lowerBound">下边界</param>
        /// <param name="basic">第一条线的横坐标</param>
        public int[] ExtractVerticalLinesL2R(Mat image, out double result, int upperBound, int lowerBound, double basic, bool cal_Jiaoneisuo = true)
        {
            int rows = image.Rows;
            int cols = image.Cols;
            int sum = 0;
            int count = 0;
            // 寻找的左右范围
            int leftBound = (int)basic + 15;
            int rightBound = (int)basic + 45;

            int countUp = 5;
            if (!cal_Jiaoneisuo) countUp = 1;
            //当点的个数少于5的时候循环
            while (count < countUp)
            {
                count = 0;
                sum = 0;
                //每次循环，寻找范围向左移动5个像素
                leftBound = leftBound + 5;
                rightBound = rightBound + 5;
                if (rightBound > image.Cols)
                    break;
                //遍历，寻找线条上的点，并记录横坐标
                for (int i = upperBound; i < lowerBound; i++)
                {//待自测scc-1
                    //bool isWhiteArea = false;//避免弧度大，导致找的位置与角落的弧度相交
                    for (int j = leftBound; j < rightBound; j++)
                    {
                        //if (!isWhiteArea)
                        //{
                        //    if (image.Get<byte>(i, j) > 0)
                        //        isWhiteArea = true;
                        //}else 
						if (image.Get<byte>(i, j) == 0)
                        {
                            sum += j;
                            count++;
                            break;
                        }
                    }
                }

            }

            leftBound = (int)basic + 15;
            rightBound = (int)basic + 145;
            if (rightBound >= cols) rightBound = cols - 1;
            double y1 = upperBound;
            double x1 = leftBound;
            for (int i = upperBound + 20; i < lowerBound - 20; i++)
            {
                for (int j = leftBound; j < rightBound; j++)
                {
                    if (image.Get<byte>(i, j) == 0)
                    {
                        if (x1 < j)
                        {
                            x1 = j;
                            y1 = i;
                        }
                        break;
                    }
                }
            }

            result = sum / count;
            return new int[] { (int)x1, (int)y1 };
        }
        /// <summary>
        /// 从右往左提取第一条竖线横坐标
        /// </summary>
        /// <param name="image">输入二值图像</param>
        /// <param name="result">输出坐标结果</param>
        /// <param name="upperBound">上边界</param>
        /// <param name="lowerBound">下边界</param>
        public void ExtractVerticalLinesR2L(Mat image, out double result, int upperBound, int lowerBound, int showMat = 0)
        {
            int rows = image.Rows;
            int cols = image.Cols;
            int sum = 0;
            int count = 0;
            int countV = 0;
            for (int i = upperBound; i < lowerBound; i++)
            {
                for (int j = cols - 1; j > 0; j--)
                {
                    if (image.Get<byte>(i, j) > 0)
                    {
                        sum += j;
                        count++;
                        break;
                    }
                }
                if (sum == 0) countV = i;
            }
            result = sum / count;
            ////对自动结果不正确（这里使用距离过远来判定）的扩展运算
            //double result1 = 0;
            if (showMat > 0 && cols - result > 20/*countV > (upperBound + lowerBound) / 2*/)
            {
                sum = 0;
                count = 0;
                //Mat imageClone = image.Clone() * 127;
                //Cv2.Line(imageClone, 0, upperBound, cols - 1, upperBound, new Scalar(255));
                //Cv2.Line(imageClone, 0, lowerBound, cols - 1, lowerBound, new Scalar(255));
                //Cv2.ImWrite(@"C:\Users\54434\Desktop\imageClone_" + showMat + ".png", imageClone);
                ////int sum = 0;
                ////int count = 0;
                bool sumAdd = false;
                for (int i = upperBound - 5; i < lowerBound + 5; i++)
                {
                    sumAdd = false;
                    for (int j = cols - 1; j > cols - 20; j--)
                    {
                        if (image.Get<byte>(i, j) > 0)
                        {
                            sumAdd = true;
                            sum += j;
                            count++;
                            break;
                        }
                    }
                    if (!sumAdd && sum > 0) 
                        break;
                }
                if (sum == 0)
                {
                    for (int i = upperBound - 5; i < lowerBound + 5; i++)
                    {
                        sumAdd = false;
                        for (int j = cols - 1; j > cols - 26; j--)
                        {
                            if (image.Get<byte>(i, j) > 0)
                            {
                                sumAdd = true;
                                sum += j;
                                count++;
                                break;
                            }
                        }
                        if (!sumAdd && sum > 0)
                            break;
                    }
                }

                // 输出平均横坐标
                if (sum > 0) 
                    result = sum / count;
            }

            //// 输出平均横坐标
            //if (true)
            //{
            //}
            //result = sum / count;
        }
        /// <summary>
        /// 提取第二条竖线的横坐标，从右往左
        /// </summary>
        /// <param name="image">输入二值图像</param>
        /// <param name="result">输出坐标结果</param>
        /// <param name="upperBound">上边界</param>
        /// <param name="lowerBound">下边界</param>
        /// <param name="basic">第一条线的横坐标</param>
        public int[] ExtractVerticalLinesR2L(Mat image, out double result, int upperBound, int lowerBound, double basic, int showMat = 0)
        {
            int rows = image.Rows;
            int cols = image.Cols;
            int sum = 0;
            int count = 0;
            // 寻找的左右范围
            int leftBound = (int)basic - 45;
            int rightBound = (int)basic - 15;

            //if (showMat > 0)
            //{
            //    Mat imageClone = image.Clone() * 127;
            //    Cv2.Line(imageClone, leftBound, upperBound, rightBound - 1, upperBound, new Scalar(255));
            //    Cv2.Line(imageClone, leftBound, lowerBound, rightBound - 1, lowerBound, new Scalar(255));
            //    Cv2.ImWrite(@"C:\Users\54434\Desktop\imageClone_" + showMat + ".png", imageClone);
            //}

            //当点的个数少于5的时候循环
            while (count < 5)
            {
                count = 0;
                sum = 0;
                //每次循环，寻找范围向左移动5个像素
                leftBound = leftBound - 5;
                rightBound = rightBound - 5;
                //遍历，寻找线条上的点，并记录横坐标
                for (int i = upperBound; i < lowerBound; i++)
                {//待自测scc-1
                    //bool isWhiteArea = false;//避免弧度大，导致找的位置与角落的弧度相交
                    ////(showMat > 0)
                    for (int j = rightBound - 1; j > leftBound; j--)
                    {
                        //if ((showMat > 0) && !isWhiteArea)
                        //{
                        //    if (image.Get<byte>(i, j) > 0)
                        //        isWhiteArea = true;
                        //}
                        //else
                        if (image.Get<byte>(i, j) == 0)
                        {
                            sum += j;
                            count++;
                            break;
                        }
                    }
                }

            }

            //if (count == 0)
            //{
            //}


            leftBound = (int)basic - 145;
            if (leftBound < 0) leftBound = 0;
            rightBound = (int)basic - 15;
            double y1 = upperBound;
            double x1 = rightBound;
            //遍历，寻找线条上的点，并记录横坐标
            for (int i = upperBound + 20; i < lowerBound - 20; i++)
            {
                for (int j = rightBound - 1; j > leftBound; j--)
                {
                    if (image.Get<byte>(i, j) == 0)
                    {
                        if (x1 > j)
                        {
                            x1 = j;
                            y1 = i;
                        }
                        break;
                    }
                }
            }

            result = sum / count;
            return new int[] { (int)x1, (int)y1 };
        }
        /// <summary>
        /// 提取三层板的粗糙度以及粗糙度的坐标
        /// </summary>
        /// <param name="imageContour">二值图像</param>
        /// <param name="imageRed">红色通道图片</param>
        /// <param name="ordinateL3">第三条横线</param>
        /// <param name="ordinateL4">第四条横线</param>
        /// <param name="ordinateL5">第五条横线</param>
        /// <param name="ordinateL6">第六条横线</param>
        /// <param name="ordinateV2">第二条竖线</param>
        /// <param name="ordinateV4">第四条竖线</param>
        /// <param name="dataArea">数据提取区域</param>
        /// <param name="direction">槽孔所在左右方向，left、right</param>
        /// <param name="roughness">输出粗糙度</param>
        /// <param name="roughnessOrdinate">输出粗糙度坐标</param>
        public void GetSancengRoughness(Mat imageContour, Mat imageRed, int ordinateL3, int ordinateL4, int ordinateL5, int ordinateL6, int ordinateV2, int ordinateV4, int[] dataArea, string direction, out int roughness, out int[] roughnessOrdinate)
        {
            int leftBorder1 = 0, rightBorder1 = 0, leftBorder2 = 0, rightBorder2 = 0;
            int range = 70;
            switch (direction)
            {
                case "right":
                    leftBorder1 = ordinateV2;
                    rightBorder1 = ordinateV2 + range;
                    leftBorder2 = ordinateV4;
                    rightBorder2 = ordinateV4 + range;
                    break;
                case "left":
                    leftBorder1 = ordinateV2 - range;
                    rightBorder1 = ordinateV2;
                    leftBorder2 = ordinateV4 - range;
                    rightBorder2 = ordinateV4;
                    break;
            }
            int sum = 0, count = 0;
            double averSaturation1 = 0, averSaturation2 = 0;
            roughness = 0;
            roughnessOrdinate = new int[4] { 0, 0, 0, 0 };
            Mat sobel = new Mat();
            Sobel(imageContour, out sobel);
            //计算粗糙度
            int max = 0;
            //先上下遍历一遍寻找最大值，避免找不到胶体
            for (int i = (int)ordinateL3 + 20; i < (int)ordinateL4 - 15; i++)
            {
                for (int j = leftBorder1; j < rightBorder1; j++)
                {
                    if (sobel.Get<byte>(i, j) > 0)
                    {
                        if (Math.Abs(j - (int)(ordinateV2)) > max)
                        {
                            max = Math.Abs(j - (int)(ordinateV2));
                            roughnessOrdinate[0] = (int)ordinateV2;
                            roughnessOrdinate[1] = i;
                            roughnessOrdinate[2] = j;
                            roughnessOrdinate[3] = i;
                        }
                    }
                }

            }

            for (int i = (int)ordinateL5 + 15; i < (int)ordinateL6 - 10; i++)
            {

                for (int j = leftBorder2; j < rightBorder2; j++)
                {
                    if (sobel.Get<byte>(i, j) > 0)
                    {
                        if (Math.Abs(j - (ordinateV4)) > max)
                        {
                            max = Math.Abs(j - (ordinateV4));
                            roughnessOrdinate[0] = (int)ordinateV4;
                            roughnessOrdinate[1] = i;
                            roughnessOrdinate[2] = j;
                            roughnessOrdinate[3] = i;
                        }
                    }
                }
            }
            roughness = max;
            if (roughness < 10)
            {
                //判断胶体方向
                Cv2.EqualizeHist(imageRed, imageRed);
                Mat upperCrop = imageRed[(int)ordinateL3 + 10, (int)ordinateL4 - 10, dataArea[0], dataArea[1]];
                Mat lowerCrop = imageRed[(int)ordinateL5 + 10, (int)ordinateL6 - 10, dataArea[0], dataArea[1]];
                //Mat duibi = new Mat(upperCrop.Size().Height + lowerCrop.Size().Height, upperCrop.Size().Width, upperCrop.Type());
                //upperCrop.CopyTo(duibi[0, upperCrop.Size().Height - 1, 0, upperCrop.Size().Width - 1]);
                //lowerCrop.CopyTo(duibi[upperCrop.Size().Height, duibi.Size().Height - 1, 0, upperCrop.Size().Width - 1]);
                //new Window("upperCrop", WindowMode.Normal, upperCrop);
                //new Window("lowerCrop", WindowMode.Normal, lowerCrop);
                //new Window("imageRed", WindowMode.Normal, imageRed);
                //Cv2.WaitKey();
                //Cv2.EqualizeHist(duibi, duibi);
                //Scalar s1 = duibi[0, upperCrop.Size().Height - 1, 0, upperCrop.Size().Width - 1].Sum();
                //Scalar s2 = duibi[upperCrop.Size().Height, duibi.Size().Height - 1, 0, upperCrop.Size().Width - 1].Sum();
                Scalar s1 = upperCrop.Sum();
                Scalar s2 = lowerCrop.Sum();
                averSaturation1 = (double)s1 / (upperCrop.Cols * upperCrop.Rows);
                averSaturation2 = (double)s2 / (lowerCrop.Cols * lowerCrop.Rows);
                for (int i = 0; i < upperCrop.Rows; i++)
                {
                    for (int j = 0; j < upperCrop.Cols; j++)
                    {
                        sum += Math.Abs(upperCrop.Get<byte>(i, j) - (int)averSaturation1);
                    }
                }
                double biaozhuncha1 = sum / (upperCrop.Cols * upperCrop.Rows);
                sum = 0;
                for (int i = 0; i < lowerCrop.Rows; i++)
                {
                    for (int j = 0; j < lowerCrop.Cols; j++)
                    {
                        sum += Math.Abs(lowerCrop.Get<byte>(i, j) - (int)averSaturation2);
                    }
                }
                double biaozhuncha2 = sum / (lowerCrop.Cols * lowerCrop.Rows);

                int direction2 = 0;
                if (biaozhuncha1 > biaozhuncha2)
                    direction2 = 0;//等于0时说明胶体在上面，否则是下面
                else
                    direction2 = 1;
                switch (direction2)
                {
                    case 0:
                        for (int i = (int)ordinateL3 + 10; i < (int)ordinateL4 - 15; i++)
                        {
                            for (int j = leftBorder1; j < rightBorder1; j++)
                            {
                                if (sobel.Get<byte>(i, j) > 0)
                                {
                                    if (Math.Abs(j - (int)(ordinateV2)) > max)
                                    {
                                        max = Math.Abs(j - (int)(ordinateV2));
                                        roughnessOrdinate[0] = (int)ordinateV2;
                                        roughnessOrdinate[1] = i;
                                        roughnessOrdinate[2] = j;
                                        roughnessOrdinate[3] = i;
                                    }
                                }
                            }
                        }
                        roughness = max;
                        break;
                    case 1:
                        for (int i = (int)ordinateL5 + 15; i < (int)ordinateL6 - 10; i++)
                        {
                            for (int j = leftBorder2; j < rightBorder2; j++)
                            {
                                if (sobel.Get<byte>(i, j) > 0)
                                {
                                    if (Math.Abs(j - (int)(ordinateV4)) > max)
                                    {
                                        max = Math.Abs(j - (int)(ordinateV4));
                                        roughnessOrdinate[0] = (int)ordinateV4;
                                        roughnessOrdinate[1] = i;
                                        roughnessOrdinate[2] = j;
                                        roughnessOrdinate[3] = i;
                                    }
                                }
                            }
                        }
                        roughness = max;
                        break;
                }
            }
        }
        /// <summary>
        /// 提取四层板的粗糙度
        /// </summary>
        /// <param name="imageContour">二值图像</param>
        /// <param name="upperBorder">上界</param>
        /// <param name="lowerBorder">下界</param>
        /// <param name="basic">边缘线</param>
        /// <param name="direction">槽孔所在左右方向，left、right</param>
        /// <param name="roughness">输出粗糙度</param>
        /// <param name="roughnessOrdinate">输出粗糙度坐标</param>
        public void GetSicengRoughness(Mat imageContour, int upperBorder, int lowerBorder, int basic, string direction, out int roughness, out int[] roughnessOrdinate)
        {
            int leftBorder = 0, rightBorder = 0;
            int range = 70;
            switch (direction)
            {
                case "right":
                    leftBorder = basic;
                    rightBorder = basic + range;
                    break;
                case "left":
                    leftBorder = basic - range;
                    rightBorder = basic;
                    break;
            }
            int max = 0;
            roughness = 0;
            roughnessOrdinate = new int[4];
            Mat sobel = new Mat();
            Sobel(imageContour, out sobel);
            for (int i = upperBorder; i < lowerBorder; i++)
            {
                for (int j = leftBorder; j < rightBorder; j++)
                {
                    if (sobel.Get<byte>(i, j) > 0)
                    {
                        if (Math.Abs(j - basic) > max)
                        {
                            max = Math.Abs(j - basic);
                            roughnessOrdinate[0] = basic;
                            roughnessOrdinate[1] = i;
                            roughnessOrdinate[2] = j;
                            roughnessOrdinate[3] = i;
                        }
                    }
                }
            }
            roughness = max;
        }
        public void GetNewKongtong(Mat imageRed, Mat imageContour, int[] leftAperture, int[] rightAperture, double leftOrdinateMiantong, int leftMiddleMianJicaitong, double leftOrdinate3, double rightOrdinateMiantong, int rightMiddleMianJicaitong, double rightOrdinate3, out double[] kongtong, out int[] leftKongtong, out int[] rightKongtong, out int[] leftPoint2, out int[] rightPoint2)
        {
            kongtong = new double[2];
            leftKongtong = new int[2];
            rightKongtong = new int[2];
            leftPoint2 = new int[2];
            rightPoint2 = new int[2];

            #region//左侧
            Mat leftCrop = imageRed[(int)leftOrdinateMiantong + 40, (int)leftOrdinate3 - 10, leftMiddleMianJicaitong, leftAperture[1]].Clone();
            Mat leftContour = new Mat();
            double t = Cv2.Threshold(leftCrop, leftContour, 0, 1, ThresholdTypes.Otsu);
            Mat leftFanse = 1 - leftContour;
            InputArray leftKernel = InputArray.Create<int>(new int[17, 17] {
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
             });
            InputArray leftKernel2 = InputArray.Create<int>(new int[17, 17] {
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1 },
             });
            InputArray leftKernel3 = InputArray.Create<int>(new int[17, 17] {
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 },
             });
            Mat leftFilter = new Mat();
            //Cv2.Filter2D(leftFanse, leftFilter, -1, leftKernel, new Point(-1, -1), 0);
            //Cv2.Filter2D(leftFanse, leftFilter, -1, leftKernel2, new Point(-1, -1), 0);
            Cv2.Filter2D(leftFanse, leftFilter, -1, leftKernel3, new Point(-1, -1), 0);
            Mat leftThresh = leftFilter.Threshold(14, 1, ThresholdTypes.Binary);
            for (int j = leftThresh.Cols - 1; j > 0; j--)//从右上角，以135°方向遍历
            {
                for (int k = j; k < leftThresh.Cols && (k - j < leftThresh.Rows); k++)
                {
                    if (leftThresh.Get<byte>(k - j, k) > 0)
                    {
                        leftKongtong[0] = k - j + (int)leftOrdinateMiantong + 40;//纵
                        leftKongtong[1] = k + leftMiddleMianJicaitong;//横
                        //Cv2.Circle(imageRed, k + leftMiddleMianJicaitong + border, k - j + (int)leftOrdinateMiantong + upper - 10, 1, 1, 1);
                        //new Window("imageRed_Line", WindowMode.Normal, imageRed);
                        break;

                    }
                }
                if (leftKongtong[0] != 0)
                    break;
            }
            #endregion
            #region//右侧
            Mat rightCrop = imageRed[(int)rightOrdinateMiantong + 40, (int)rightOrdinate3 - 10, rightAperture[1], rightMiddleMianJicaitong].Clone();
            Mat rightContour = new Mat();
            double t1 = Cv2.Threshold(rightCrop, rightContour, 0, 1, ThresholdTypes.Otsu);
            Mat rightFanse = 1 - rightContour;
            InputArray rightKernel = InputArray.Create<int>(new int[17, 17] {
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
             });
            InputArray rightKernel2 = InputArray.Create<int>(new int[17, 17] {
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1 },
            { 0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
             });
            InputArray rightKernel3 = InputArray.Create<int>(new int[17, 17] {
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1 },
            { 0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
             });
            Mat rightFilter = new Mat();
            //Cv2.Filter2D(rightFanse, rightFilter, -1, rightKernel, new Point(-1, -1), 0);
            //Cv2.Filter2D(rightFanse, rightFilter, -1, rightKernel2, new Point(-1, -1), 0);
            Cv2.Filter2D(rightFanse, rightFilter, -1, rightKernel3, new Point(-1, -1), 0);
            Mat rightThresh = rightFilter.Threshold(14, 1, ThresholdTypes.Binary);
            for (int j = 0; j < rightThresh.Cols; j++)//从左上角，45°方向遍历
            {
                for (int k = j; k >= 0 && j - k < rightThresh.Rows; k--)
                {
                    if (rightThresh.Get<byte>(j - k, k) > 0)
                    {
                        rightKongtong[0] = j - k + (int)rightOrdinateMiantong + 40;
                        rightKongtong[1] = k + rightAperture[1];
                        //Cv2.Circle(imageRed, k + rightAperture[1], k - j + (int)rightOrdinateMiantong + upper - 10, 1, 1, 1);
                        //new Window("imageRed_Line", WindowMode.Normal, imageRed);
                        break;
                    }
                }
                if (rightKongtong[0] != 0)
                    break;

            }
            #endregion
            //ImageShow(leftCrop, leftContour * 255, /*rightContour * 255, */leftThresh * 255/*, rightThresh * 255*/);
            //Cv2.Circle(imageRed, new Point(leftKongtong[1], leftKongtong[0]), 10, new Scalar(0), 2);
            //Cv2.Circle(imageRed, new Point(rightKongtong[1], rightKongtong[0]), 10, new Scalar(0), 2);
            ////ImageShow(imageRed);

            GetKongtong(imageContour, leftKongtong, rightKongtong, out kongtong, out leftPoint2, out rightPoint2);
            //LineShow(imageRed, leftKongtong[1], leftKongtong[0], leftPoint2[1], leftPoint2[0]);
            //LineShow(imageRed, rightKongtong[1], rightKongtong[0], rightPoint2[1], rightPoint2[0]);
            //ImageShow(imageRed);
            //leftKongtong[0] -= upper;
            //rightKongtong[0] -= upper;
            //leftPoint2[0] -= upper;
            //rightPoint2[0] -= upper;

            if(rightFilter != null)
            {
                rightFilter.Dispose();
            }
        }
        /// <summary>
        /// 计算孔铜
        /// </summary>
        /// <param name="imageContour">二值图</param>
        /// <param name="apertureBegin">左孔径坐标</param>
        /// <param name="apertureEnd">右孔径坐标</param>
        /// <param name="kongtong">输出左右孔铜的距离</param>
        /// <param name="pointLeft">左孔铜对应边缘线的坐标</param>
        /// <param name="pointRight">右孔铜对应边缘线的坐标</param>
        public void GetKongtong(Mat imageContour, int[] apertureBegin, int[] apertureEnd, out double[] kongtong, out int[] pointLeft, out int[] pointRight)
        {
            //曲面上点的坐标
            int count = apertureEnd[1] - apertureBegin[1];
            int[,] coordinate = new int[Math.Abs(apertureEnd[1] - apertureBegin[1]), 2];//先纵坐标后横坐标
            for (int j = apertureBegin[1]; j < apertureEnd[1]; j++)
            {
                for (int i = 0; i < imageContour.Rows; i++)
                {
                    if (imageContour.Get<byte>(i, j) > 0)
                    {
                        coordinate[j - apertureBegin[1], 0] = i;
                        coordinate[j - apertureBegin[1], 1] = j;
                        break;
                    }
                }
            }

            //计算距离,最小的距离分别为左孔铜和右孔铜
            double leftKongtong = 1000;
            double rightKongtong = 1000;
            double distance1 = 0;
            double distance2 = 0;
            //当距离最短是曲线上点的坐标，第一列是纵坐标（行数），第二列是横坐标（列数）
            pointLeft = new int[2];
            pointRight = new int[2];
            for (int i = 0; i < count; i++)
            {
                //计算曲面点到左起始点的距离
                if (i < count / 2)
                {
                    distance1 = Math.Sqrt(Math.Pow((coordinate[i, 0] - apertureBegin[0]), 2) + Math.Pow((coordinate[i, 1] - apertureBegin[1]), 2));
                    //计算曲面点到右截止点的距离
                    if (leftKongtong > distance1)
                    {
                        leftKongtong = distance1;
                        pointLeft[0] = coordinate[i, 0];
                        pointLeft[1] = coordinate[i, 1];
                    }
                }
                else
                {
                    distance2 = Math.Sqrt(Math.Pow((coordinate[i, 0] - apertureEnd[0]), 2) + Math.Pow((coordinate[i, 1] - apertureEnd[1]), 2));
                    //得到左右孔铜以及对应的曲面坐标
                    if (rightKongtong > distance2)
                    {
                        rightKongtong = distance2;
                        pointRight[0] = coordinate[i, 0];
                        pointRight[1] = coordinate[i, 1];
                    }
                }
            }
            kongtong = new double[2] { leftKongtong, rightKongtong };
        }
        public void ShenmangkongNewKongtong(Mat image, Mat imageContour, int leftL2, int rightL2, int[] leftAperture, int[] rightAperture, out double[] kongtong, out int[] leftKongtong, out int[] rightKongtong, out int[] leftPoint2, out int[] rightPoint2)
        {
            kongtong = new double[2];
            leftKongtong = new int[2];
            rightKongtong = new int[2];
            leftPoint2 = new int[2];
            rightPoint2 = new int[2];
            #region//左
            Mat leftCrop = image[leftL2 - 10, leftL2 + 20, leftAperture[1] - 30, leftAperture[1] + 5].Clone();
            Mat leftThresh = leftCrop.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat leftFanse = 1 - leftThresh;
            InputArray leftKernel = InputArray.Create<int>(new int[17, 17] {
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            { -1,-1,-1,-1,-1,-1,-1,-1,-1,-1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
            {  1, 1, 1, 1, 1, 1, 1, 1, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
             });
            InputArray leftKernel2 = InputArray.Create<int>(new int[17, 17] {
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0 },
            { 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1 },
             });
            Mat leftFilter1 = new Mat();
            Cv2.Filter2D(leftFanse, leftFilter1, -1, leftKernel, new Point(-1, -1), 0);
            Mat leftFilter2 = new Mat();
            Cv2.Filter2D(leftFanse, leftFilter2, -1, leftKernel2, new Point(-1, -1), 0);
            Mat leftFilter = new Mat();
            Cv2.AddWeighted(leftFilter1, 0, leftFilter2, 1, 0, leftFilter);
            Cv2.Rectangle(leftFilter, new Rect(0, 0, leftFilter.Cols, 5), new Scalar(0), -1);
            Cv2.Rectangle(leftFilter, new Rect(0, 15, leftFilter.Cols, leftFilter.Rows - 15), new Scalar(0), -1);
            double min, max;
            Cv2.MinMaxIdx(leftFilter, out min, out max);
            Mat leftFilterThresh = leftFilter.Threshold(max - 2, 1, ThresholdTypes.Binary);
            Cv2.Flip(leftFilterThresh, leftFilterThresh, FlipMode.Y);
            Point left;
            FindLeftTop(leftFilterThresh, out left);
            leftKongtong[0] = left.Y + leftL2 - 10;
            leftKongtong[1] = leftCrop.Cols - left.X + leftAperture[1] - 30;
            Mat newLeft = leftFilterThresh.Clone();
            newLeft.Set<byte>(left.Y, left.X, 255);
            //ImageShow(leftCrop, leftFilter * 50, leftFilterThresh * 255, newLeft);
            #endregion
            #region//右
            Mat rightCrop = image[rightL2 - 10, rightL2 + 20, rightAperture[1] - 5, rightAperture[1] + 30].Clone();
            Mat rightThresh = rightCrop.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat rightFanse = 1 - rightThresh;
            InputArray rightKernel = InputArray.Create<int>(new int[17, 17] {
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1 },
            {  0, 0, 0, 0, 0, 0, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0,-1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1 },
            {  0, 0, 0, 0, 0,-1, 0,-1, 0, 1, 1, 1, 1, 1, 1, 1, 1 },
            {  0, 0, 0, 0,-1, 0, 1,-1, 0, 1, 1,-1,-1,-1,-1,-1,-1 },
            {  0, 0, 0,-1, 0, 1, 0,-1, 0, 1, 1,-1,-1,-1,-1,-1,-1 },
            {  0, 0,-1, 0, 1, 0, 0,-1, 0, 1, 1,-1,-1,-1,-1,-1,-1 },
            {  0,-1, 0, 1, 0, 0, 0,-1, 0, 1, 1,-1,-1,-1,-1,-1,-1 },
            { -1, 0, 1, 0, 0, 0, 0,-1, 0, 1, 1,-1,-1,-1,-1,-1,-1 },
            {  0, 1, 0, 0, 0, 0, 0,-1, 0, 1, 1,-1,-1,-1,-1,-1,-1 },
             });
            InputArray rightKernel2 = InputArray.Create<int>(new int[17, 17] {
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1 },
            { 0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
            { 1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 },
             });
            Mat rightFilter1 = new Mat();
            Cv2.Filter2D(rightFanse, rightFilter1, -1, rightKernel, new Point(-1, -1), 0);
            Mat rightFilter2 = new Mat();
            Cv2.Filter2D(rightFanse, rightFilter2, -1, rightKernel2, new Point(-1, -1), 0);
            Mat rightFilter = new Mat();
            Cv2.AddWeighted(rightFilter1, 0, rightFilter2, 1, 0, rightFilter);
            Cv2.Rectangle(rightFilter, new Rect(0, 0, rightFilter.Cols, 5), new Scalar(0), -1);
            Cv2.Rectangle(rightFilter, new Rect(0, 15, rightFilter.Cols, rightFilter.Rows - 15), new Scalar(0), -1);
            Cv2.MinMaxIdx(rightFilter, out min, out max);
            Mat rightFilterThresh = rightFilter.Threshold(max - 2, 1, ThresholdTypes.Binary);
            Point right;
            FindLeftTop(rightFilterThresh, out right);
            rightKongtong[0] = right.Y + rightL2 - 10;
            rightKongtong[1] = right.X + rightAperture[1] - 5;
            Mat newRight = rightFilterThresh.Clone();
            newRight.Set<byte>(right.Y, right.X, 255);
            //ImageShow(rightCrop, rightThresh * 255, rightFilter2 * 50, rightFilterThresh * 255, newRight);
            #endregion
            #region//边缘线
            GetKongtong(imageContour, leftKongtong, rightKongtong, out kongtong, out leftPoint2, out rightPoint2);
            #endregion
        }
        /// <summary>
        /// 计算最小孔环，从外侧交点到上孔径
        /// </summary>
        /// <param name="imageContour"></param>
        /// <param name="upper"></param>
        /// <param name="lower"></param>
        /// <param name="leftBorder"></param>
        /// <param name="rightBorder"></param>
        /// <param name="pointRing"></param>
        /// <param name="direction"></param>
        public void GetMinmumRing(Mat imageContour, int upper, int lower, int leftBorder, int rightBorder, out int[] pointRing, string direction)
        {
            pointRing = new int[2];
            Mat crop2 = imageContour[upper, lower, leftBorder, rightBorder].Clone();
            Scalar sum = new Scalar(0);
            Scalar lastSum = new Scalar(0);
            switch (direction)
            {
                case "left":
                    //for (int j = 0; j < crop2.Cols - 1; j += 5)
                    //{
                    //    sum = crop2[0, crop2.Rows, j, j + 1].Sum();
                    //    if ((int)lastSum != 0 && (int)sum-(int)lastSum>10)
                    //    {
                    //        pointRing[1] = j+leftBorder-2;
                    //        break;
                    //    }
                    //    lastSum = sum;
                    //}
                    for (int j = crop2.Cols - 1; j > 1; j -= 10)
                    {
                        sum = crop2[0, crop2.Rows, j - 1, j].Sum();
                        if ((int)lastSum != 0 && (int)lastSum - (int)sum > 10)
                        {
                            pointRing[1] = j + leftBorder - 5;
                            break;
                        }
                        lastSum = sum;
                    }
                    break;
                case "right":
                    //for (int j = crop2.Cols - 1; j > 2; j -= 5)
                    //{
                    //    sum = crop2[0, crop2.Rows, j - 1, j].Sum();
                    //    if ((int)lastSum != 0 && (int)sum - (int)lastSum > 10)
                    //    {
                    //        pointRing[1] = j + leftBorder+2;
                    //        break;
                    //    }
                    //    lastSum = sum;
                    //}
                    for (int j = 1; j < crop2.Cols - 1; j += 10)
                    {
                        sum = crop2[0, crop2.Rows, j, j + 1].Sum();
                        if ((int)lastSum != 0 && (int)lastSum - (int)sum > 10)
                        {
                            pointRing[1] = j + leftBorder + 5;
                            break;
                        }
                        lastSum = sum;
                    }
                    break;
            }
            //ImageShow(crop2 * 255);
            //int j = 0;
            //for (int i = crop2.Rows-1;i>0;i--)
            //{
            //    for (int k = i; k < crop2.Rows&&(crop2.Cols-1-(k-i))>0; k++)
            //    {
            //        j = crop2.Cols - 1 - (k - i);
            //        if (crop2.Get<byte>(k, j) > 0)
            //        {
            //            pointLeftRing[0] = k + upper;
            //            pointLeftRing[1] = j ;
            //            break;
            //        }
            //    }
            //}
            //ImageShow(filter * 30, thresh * 255,crop*255,crop2*255);

        }
        /// <summary>
        /// 得到边缘线上拐点的坐标
        /// </summary>
        /// <param name="imageContour">二值图</param>
        /// <param name="apertureBegin">左孔径坐标</param>
        /// <param name="apertureEnd">右孔径坐标</param>
        /// <param name="curveVertex">输出拐点坐标,0:縱坐標；1：橫坐標</param>
        /// <param name="middleApertureY">孔径对应边缘线上点的平均纵坐标</param>
        public void CurveVertex(Mat imageContour, int[] apertureBegin, int[] apertureEnd, out int[] curveVertex, out double middleApertureY)
        {
            //曲面顶点的坐标
            curveVertex = new int[2];
            //孔径平均横坐标
            double middleAperture = (apertureBegin[1] + apertureEnd[1]) / 2;
            //孔径平均高度
            int[] apertureY = new int[2];
            for (int i = 0; i < imageContour.Rows; i++)
            {
                if (imageContour.Get<byte>(i, apertureBegin[1]) > 0)
                {
                    apertureY[0] = i;
                    break;
                }
            }
            for (int i = 0; i < imageContour.Rows; i++)
            {
                if (imageContour.Get<byte>(i, apertureEnd[1]) > 0)
                {
                    apertureY[1] = i;
                    break;
                }
            }
            middleApertureY = (apertureY[0] + apertureY[1]) / 2;

            //边缘线坐标

            int count = Math.Abs((apertureEnd[1] - apertureBegin[1]) / 2);
            int[,] ordinate = new int[count, 2];
            int range = apertureEnd[1] - apertureBegin[1];
            for (int j = range / 4 + apertureBegin[1]; j < range / 4 + apertureBegin[1] + count; j++)
            {
                for (int i = 0; i < imageContour.Rows; i++)
                {
                    if (imageContour.Get<byte>(i, j) > 0)
                    {
                        ordinate[j - apertureBegin[1] - range / 4, 0] = i;
                        ordinate[j - apertureBegin[1] - range / 4, 1] = j;
                        break;
                    }
                }
            }
            //孔深,取曲面上的点到孔径平均高度只差的最大值
            double kongshenAomian = 0;//当边缘线内凹或外凸，孔深最大值
            //double kongshenTumian = 1000;//当边缘线内凸，孔深最小值
            int[] coordinateAomian = new int[2];
            //int[] coordinateTumian = new int[2];
            double t = 0;
            for (int i = 0; i < count; i++)
            {
                t = Math.Abs(middleApertureY - ordinate[i, 0]);
                if (kongshenAomian < t)
                {
                    kongshenAomian = t;
                    coordinateAomian[0] = ordinate[i, 0];
                    coordinateAomian[1] = ordinate[i, 1];
                }
                //if (kongshenTumian > t)
                //{
                //    kongshenTumian = t;
                //    coordinateTumian[0] = ordinate[i, 0];
                //    coordinateTumian[1] = ordinate[i, 1];
                //}
            }
            curveVertex = coordinateAomian;
            //判断哪个点离孔径中心更近,更近的为曲面坐标
            //double absAomian = Math.Abs(coordinateAomian[1] - middleAperture);
            //double absTumian = Math.Abs(coordinateTumian[1] - middleAperture);
            //if (absAomian < absTumian)
            //{
            //    curveVertex = coordinateAomian;
            //}
            //else
            //{
            //    curveVertex = coordinateTumian;
            //}
        }
        public void ShenmangkongShangkongjing(Mat contour, int leftL3, int rightL3, int[] lowerAperture, out int[] leftAperture, out int[] rightAperture)
        {
            #region//左
            Mat cropLeft = contour[leftL3 - 20, leftL3 + 20, (lowerAperture[0] - 200)<0?0:(lowerAperture[0] - 200), lowerAperture[0] + 200].Clone();
            InputArray leftKernel = InputArray.Create<int>(new int[17, 17] {
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 },
            { -1,-1,-1,-1,-1,-1,-1,-1, 0, 1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0,-1, 0, 1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0,-1, 0, 1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0,-1, 0, 1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0,-1, 0, 1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0,-1, 0, 1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0,-1, 0, 1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0,-1, 0, 1, 0, 0, 0, 0, 0, 0, 0 },
             });
            Mat leftFilter = new Mat();
            Cv2.Filter2D(cropLeft, leftFilter, -1, leftKernel, new Point(-1, -1), 0);
            double min2, max;
            Cv2.MinMaxIdx(leftFilter, out min2, out max);
            Mat leftThresh = leftFilter.Threshold(max - 2, 1, ThresholdTypes.Binary);
            Cv2.Flip(leftThresh, leftThresh, FlipMode.Y);
            leftAperture = new int[2];
            int min = 100000;
            Point[] leftIdx;
            FindNonZeros(leftThresh, out leftIdx);
            for (int i = 0; i < leftIdx.Length; i++)
            {
                if (min > (leftIdx[i].X + leftIdx[i].Y))
                {
                    min = leftIdx[i].X + leftIdx[i].Y;
                    leftAperture[1] = leftThresh.Cols - leftIdx[i].X;
                    leftAperture[0] = leftIdx[i].Y;
                }
            }
            leftAperture[1] += lowerAperture[0] - 200;
            leftAperture[0] += leftL3 - 20;
            #endregion
            #region//右
            Mat cropRight = contour[rightL3 - 20, rightL3 + 20, lowerAperture[1] - 200, lowerAperture[1] + 200].Clone();
            InputArray rightKernel = InputArray.Create<int>(new int[17, 17] {
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0,-1,-1,-1,-1,-1,-1,-1,-1 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
            {  0, 0, 0, 0, 0, 0, 0, 1, 0,-1, 0, 0, 0, 0, 0, 0, 0 },
             });
            Mat rightFilter = new Mat();
            Cv2.Filter2D(cropRight, rightFilter, -1, rightKernel, new Point(-1, -1), 0);

            Cv2.MinMaxIdx(rightFilter, out min2, out max);
            Mat rightThresh = rightFilter.Threshold(max - 2, 1, ThresholdTypes.Binary);
            rightAperture = new int[2];
            Point[] rightIdx;
            FindNonZeros(rightThresh, out rightIdx);
            min = 1000000;
            for (int i = 0; i < rightIdx.Length; i++)
            {
                if (min > (rightIdx[i].X + rightIdx[i].Y))
                {
                    min = rightIdx[i].X + rightIdx[i].Y;
                    rightAperture[1] = rightIdx[i].X;
                    rightAperture[0] = rightIdx[i].Y;
                }
            }
            rightAperture[1] += lowerAperture[1] - 200;
            rightAperture[0] += rightL3 - 20;
            #endregion
            //ImageShow( cropRight * 255, rightThresh * 255);
        }
        /// <summary>
        /// 得到深盲孔的下孔径
        /// </summary>
        /// <param name="imageContour">二值图像</param>
        /// <param name="aperture">输出下孔径</param>
        /// <param name="leftUpper">左边计算区域的上边界</param>
        /// <param name="rightUpper">右边计算区域的上边界</param>
        /// <param name="leftLower">左边计算区域的下边界</param>
        /// <param name="rightLower">右边计算区域的下边界</param>
        /// <param name="dataArea">数据提取区域</param>
        public void GetShenmangLowerAperture(Mat imageContour, out int[] aperture, int leftUpper, int rightUpper, int leftLower, int rightLower, int[] dataArea)
        {
            //孔径起始点
            aperture = new int[2];
            aperture[0] = 0;
            aperture[1] = 0;
            int middle = (dataArea[1] + dataArea[2]) / 2;
            Mat fanse = 1 - imageContour;
            //Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            //Mat open = new Mat();
            //Cv2.MorphologyEx(fanse, open,MorphTypes.Open, se);
            //fanse = open;
            for (int j = middle; j > dataArea[0]; j--)
            {
                for (int i = leftUpper - 20 < 0 ? 0 : leftUpper - 20; i < leftLower - 20; i++)
                {
                    if (fanse.Get<byte>(i, j) > 0)
                    {
                        aperture[0] = j;
                        break;
                    }
                }
                if (aperture[0] != 0)
                    break;
            }
            for (int j = middle; j < dataArea[3]; j++)
            {
                for (int i = rightUpper - 20 < 0 ? 0 : rightUpper - 20; i < rightLower - 20; i++)
                {
                    if (fanse.Get<byte>(i, j) > 0)
                    {
                        aperture[1] = j;
                        break;
                    }
                }
                if (aperture[1] != 0)
                    break;
            }
        }
        /// <summary>
        /// 下孔径新方法，用胶体部分置1，向中间遍历，为0时下孔径
        /// </summary>
        /// <param name="imageContour"></param>
        /// <param name="aperture"></param>
        /// <param name="leftUpper"></param>
        /// <param name="rightUpper"></param>
        /// <param name="leftLower"></param>
        /// <param name="rightLower"></param>
        /// <param name="dataArea"></param>
        public void GetLowerAperture(Mat imageContour, out int[] aperture, int leftUpper, int rightUpper, int leftLower, int rightLower, int[] dataArea)
        {
            aperture = new int[2];
            int middle = (dataArea[1] + dataArea[2]) / 2;
            Mat fill = new Mat();
            Fill(imageContour, out fill, 1);
            Mat fanse = 1 - fill;
            Scalar sum = fanse.Sum();
            if ((int)sum != 0)
            {
                imageContour = fill.Clone();
            }
            Mat result = 1 - imageContour;
            Scalar sumLeft = new Scalar(0);
            for (int j = dataArea[0]; j < middle; j++)
            {
                sumLeft = result[leftUpper<0?0: leftUpper, leftLower, j, j + 1].Sum();
                if ((int)sumLeft == 0)
                {
                    aperture[0] = j;
                    break;
                }
            }
            Scalar sumRight = new Scalar(0);
            for (int j = dataArea[3]; j > middle; j--)
            {
                sumRight = result[rightUpper, rightLower, j - 1, j].Sum();
                if ((int)sumRight == 0)
                {
                    aperture[1] = j;
                    break;
                }
            }
            if(fill != null)
            {
                fill.Dispose();
            }
        }
		
		
        public void GetShenmangLowerAperture2(Mat imageContour, out int[] aperture, int leftUpper, int rightUpper, int leftLower, int rightLower, int[] dataArea)
        {
            aperture = new int[2] { 0, 0 };
            int middle = (dataArea[1] + dataArea[2]) / 2;
            Mat fanse = 1 - imageContour;
            int offset = 20;
            int sum = 0;
            for (int j = dataArea[1]; j < middle; j++)
            {
                sum = 0;
                for (int i = leftUpper - offset; i < leftLower - offset; i++)
                {
                    sum += fanse.Get<byte>(i, j);
                    if (fanse.Get<byte>(i, j) > 0)
                        break;
                }
                if (sum == 0)
                {
                    aperture[0] = j;
                    break;
                }
            }
            for (int j = dataArea[2]; j > middle; j--)
            {
                sum = 0;
                for (int i = rightUpper - offset; i < rightLower - offset; i++)
                {
                    sum += fanse.Get<byte>(i, j);
                    if (fanse.Get<byte>(i, j) > 0)
                        break;
                }
                if (sum == 0)
                {
                    aperture[1] = j;
                    break;
                }
            }
        }
        /// <summary>
        /// 得到深盲孔的胶线
        /// </summary>
        /// <param name="image">输入图像，一般是绿色通道</param>
        /// <param name="glueOrdinate">输出胶线纵坐标</param>
        /// <param name="leftUpper">左边上界</param>
        /// <param name="leftLower">左边下界</param>
        /// <param name="rightUpper">右边上界</param>
        /// <param name="rightLower">右边下界</param>
        /// <param name="dataArea">提取区域</param>
        public void GetGlue(Mat image, out int[] glueOrdinate, int leftUpper, int leftLower, int rightUpper, int rightLower, int[] dataArea)
        {
            glueOrdinate = new int[2];
            int[] maybePosition = new int[2];
            //int[] zero = new int[2];
            InputArray kernel = InputArray.Create<int>(new int[3, 3] { { 0, -1, 0 }, { -1, 5, -1 }, { 0, -1, 0 } });
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Mat seDilate = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 1));

            Mat crop1 = image[leftUpper, leftLower, dataArea[0], dataArea[1]];
            //将裁剪区域改为面铜+基材铜附近
            //int leftMiddleMiantong_Jicaitong = (dataArea[0] + dataArea[1]) / 2;
            //Mat crop1 = image[leftUpper, leftLower, leftMiddleMiantong_Jicaitong - 10, leftMiddleMiantong_Jicaitong + 10];
            Mat filter1 = new Mat();
            Cv2.Filter2D(crop1, filter1, -1, kernel);
            Cv2.ConvertScaleAbs(filter1, filter1);
            Mat thresh1 = 1 - filter1.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat open1 = new Mat();
            Cv2.MorphologyEx(thresh1, open1, MorphTypes.Open, seOpen);
            Cv2.MorphologyEx(open1, open1, MorphTypes.Close, seOpen);
            Cv2.Dilate(open1, open1, seDilate);
            Fill(open1, out open1, 1);
            //new Window("crop1", WindowMode.Normal, crop1);
            //new Window("thresh2", WindowMode.Normal, 255 - crop1.Threshold(0, 255, ThresholdTypes.Otsu));
            //new Window("thresh1", WindowMode.Normal, thresh1 * 255);
            //new Window("end", WindowMode.Normal, open1 * 255);
            //Cv2.WaitKey();
            Scalar sum1 = new Scalar(0);
            Scalar lastSum1 = new Scalar(0);
            Scalar sub1 = new Scalar(0);
            Scalar subMax1 = new Scalar(0);
            Scalar max1 = new Scalar(0);
            Scalar zero1 = new Scalar(0);
            for (int i = 2; i < crop1.Rows - 2; i++)
            {
                sum1 = open1[i, i + 2, 0, open1.Cols - 1].Sum();
                lastSum1 = open1[i - 2, i, 0, open1.Cols - 1].Sum();
                //zero1 = open1[i - 1, i, 0, open1.Cols - 1].Sum();
                sub1 = Math.Abs((int)sum1 - (int)lastSum1);
                if ((int)max1 < (int)sum1)
                {
                    max1 = sum1;
                    glueOrdinate[0] = i + leftUpper;
                }
                if ((int)subMax1 < (int)sub1)
                {
                    subMax1 = sub1;
                    maybePosition[0] = i + leftUpper;
                }
                //if ((int)zero1 < 10)
                //{
                //    zero[0] = i + leftUpper;
                //}
            }

            Mat crop2 = image[rightUpper, rightLower, dataArea[2], dataArea[3]];
            ////将裁剪区域改为面铜+基材铜附近
            //int rightMiddleMiantong_Jicaitong = (dataArea[2] + dataArea[3]) / 2;
            //Mat crop2 = image[rightUpper, rightLower, rightMiddleMiantong_Jicaitong - 10, rightMiddleMiantong_Jicaitong + 10];
            Mat filter2 = new Mat();
            Cv2.Filter2D(crop2, filter2, -1, kernel);
            Cv2.ConvertScaleAbs(filter2, filter2);
            Mat thresh2 = 1 - filter2.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat open2 = new Mat();
            Cv2.MorphologyEx(thresh2, open2, MorphTypes.Open, seOpen);
            Cv2.MorphologyEx(open2, open2, MorphTypes.Close, seOpen);
            Cv2.Dilate(open2, open2, seDilate);
            Fill(open2, out open2, 1);
            //new Window("thresh2", WindowMode.Normal, thresh2 * 255);
            //new Window("end2", WindowMode.Normal, open2 * 255);
            //Cv2.WaitKey();
            Scalar sum2 = new Scalar(0);
            Scalar lastSum2 = new Scalar(0);
            Scalar sub2 = new Scalar(0);
            Scalar subMax2 = new Scalar(0);
            Scalar max2 = new Scalar(0);
            Scalar zero2 = new Scalar(0);
            for (int i = 2; i < crop2.Rows - 2; i++)
            {
                sum2 = open2[i, i + 2, 0, open2.Cols - 1].Sum();
                lastSum2 = open2[i - 2, i, 0, open2.Cols - 1].Sum();
                //zero2 = open2[i - 1, i, 0, open2.Cols - 1].Sum();
                sub2 = Math.Abs((int)sum2 - (int)lastSum2);
                if ((int)max2 < (int)sum2)
                {
                    max2 = sum2;
                    glueOrdinate[1] = i + rightUpper;
                }
                if ((int)subMax2 < (int)sub2)
                {
                    subMax2 = sub2;
                    maybePosition[1] = i + rightUpper;
                }
                //if ((int)zero2 < 10)
                //{
                //    zero[1] = i + rightUpper;
                //}
            }

            if (glueOrdinate[0] > maybePosition[0])
            {
                for (int j = maybePosition[0] - leftUpper; j < glueOrdinate[0] - leftUpper; j++)
                {
                    if ((int)open1[j, j + 1, 0, open1.Cols - 1].Sum() == 0)
                    {
                        sum1 = new Scalar(0);
                        lastSum1 = new Scalar(0);
                        sub1 = new Scalar(0);
                        subMax1 = new Scalar(0);
                        max1 = new Scalar(0);
                        for (int i = maybePosition[0] - leftUpper + 2; i < crop1.Rows - 2; i++)
                        {
                            sum1 = open1[i, i + 2, 0, open1.Cols - 1].Sum();
                            lastSum1 = open1[i - 2, i, 0, open1.Cols - 1].Sum();
                            sub1 = Math.Abs((int)sum1 - (int)lastSum1);
                            if ((int)max1 < (int)sum1)
                            {
                                max1 = sum1;
                                glueOrdinate[0] = i + leftUpper;
                            }
                            if ((int)subMax1 < (int)sub1)
                            {
                                subMax1 = sub1;
                                maybePosition[0] = i + leftUpper;
                            }
                        }
                        break;
                    }
                }
                if (glueOrdinate[0] > maybePosition[0])
                {
                    //if (Math.Abs(zero[0] - maybePosition[0]) > 15&&zero[0]>10)
                    //    glueOrdinate[0] = zero[0];
                    //else
                    glueOrdinate[0] = maybePosition[0];
                }
            }
            if (glueOrdinate[1] > maybePosition[1])
            {
                for (int j = maybePosition[1] - rightUpper; j < glueOrdinate[1] - rightUpper; j++)
                {
                    if ((int)open2[j, j + 1, 0, open2.Cols - 1].Sum() == 0)
                    {
                        sum2 = new Scalar(0);
                        lastSum2 = new Scalar(0);
                        sub2 = new Scalar(0);
                        subMax2 = new Scalar(0);
                        max2 = new Scalar(0);
                        for (int i = maybePosition[1] - rightUpper + 2; i < crop2.Rows - 2; i++)
                        {
                            sum2 = open2[i, i + 2, 0, open2.Cols - 1].Sum();
                            lastSum2 = open2[i - 2, i, 0, open2.Cols - 1].Sum();
                            sub2 = Math.Abs((int)sum2 - (int)lastSum2);
                            if ((int)max2 < (int)sum2)
                            {
                                max2 = sum2;
                                glueOrdinate[1] = i + rightUpper;
                            }
                            if ((int)subMax2 < (int)sub2)
                            {
                                subMax2 = sub2;
                                maybePosition[1] = i + rightUpper;
                            }
                        }
                        break;
                    }
                }
                if (glueOrdinate[1] > maybePosition[1])
                {
                    //if (Math.Abs(zero[1] - maybePosition[1]) > 15&&zero[1]>10)
                    //    glueOrdinate[1] = zero[1];
                    //else
                    glueOrdinate[1] = maybePosition[1];
                }
            }

            //LineShow(crop1, 10, glueOrdinate[0] - leftUpper, 20, glueOrdinate[0] - leftUpper);
            //new Window("crop1", WindowMode.Normal, crop1);
            //new Window("thresh1", WindowMode.Normal, open1 * 255);
            //new Window("thresh2", WindowMode.Normal, open2 * 255);
            //Cv2.WaitKey();
        }
        /// <summary>
        /// 计算胶线坐标，修改了判定时条件，先用于深盲孔双层
        /// </summary>
        /// <param name="image"></param>
        /// <param name="glueOrdinate"></param>
        /// <param name="leftUpper"></param>
        /// <param name="leftLower"></param>
        /// <param name="rightUpper"></param>
        /// <param name="rightLower"></param>
        /// <param name="dataArea"></param>
        public void GetGlue2(Mat image, out int[] glueOrdinate, int leftUpper, int leftLower, int rightUpper, int rightLower, int[] dataArea)
        {
            glueOrdinate = new int[2];
            int[] maybePosition = new int[2];
            //int[] zero = new int[2];
            InputArray kernel = InputArray.Create<int>(new int[3, 3] { { 0, -1, 0 }, { -1, 5, -1 }, { 0, -1, 0 } });
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Mat seDilate = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));

            int width1 = dataArea[1] - dataArea[0];
            Mat crop1 = image[leftUpper, leftLower, dataArea[0], dataArea[1]];
            if (width1 > 50)
            {
                crop1 = image[leftUpper, leftLower, dataArea[0] + (width1 - 50) / 2, dataArea[1] - (width1 - 50) / 2];
                width1 = 50;
            }
            //将裁剪区域改为面铜+基材铜附近
            //int leftMiddleMiantong_Jicaitong = (dataArea[0] + dataArea[1]) / 2;
            //Mat crop1 = image[leftUpper, leftLower, leftMiddleMiantong_Jicaitong - 10, leftMiddleMiantong_Jicaitong + 10];
            int areaSize1 = crop1.Rows * crop1.Cols;
            Mat filter1 = new Mat();
            Cv2.Filter2D(crop1, filter1, -1, kernel);
            Cv2.ConvertScaleAbs(filter1, filter1);
            Mat thresh1 = 1 - filter1.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat open1 = new Mat();
            Cv2.MorphologyEx(thresh1, open1, MorphTypes.Open, seOpen);
            Cv2.MorphologyEx(open1, open1, MorphTypes.Close, seOpen);
            Cv2.Dilate(open1, open1, seDilate);
            Fill(open1, out open1, 1);
            Scalar area1 = open1.Sum();
            while ((int)area1 > areaSize1 * 0.9)
            {
                leftUpper += 5;
                crop1 = image[leftUpper, leftLower, dataArea[0], dataArea[1]];
                if (width1 > 50)
                {
                    crop1 = image[leftUpper, leftLower, dataArea[0] + (width1 - 50) / 2, dataArea[1] - (width1 - 50) / 2];
                    width1 = 50;
                }
                filter1 = new Mat();
                Cv2.Filter2D(crop1, filter1, -1, kernel);
                Cv2.ConvertScaleAbs(filter1, filter1);
                thresh1 = 1 - filter1.Threshold(0, 1, ThresholdTypes.Otsu);
                open1 = new Mat();
                Cv2.MorphologyEx(thresh1, open1, MorphTypes.Open, seOpen);
                Cv2.MorphologyEx(open1, open1, MorphTypes.Close, seOpen);
                Cv2.Dilate(open1, open1, seDilate);
                Fill(open1, out open1, 1);
                areaSize1 = crop1.Rows * crop1.Cols;
                area1 = open1.Sum();
            }
            //new Window("crop1", WindowMode.Normal, crop1);
            ////new Window("thresh2", WindowMode.Normal, 255 - crop1.Threshold(0, 255, ThresholdTypes.Otsu));
            //new Window("thresh1", WindowMode.Normal, thresh1 * 255);
            //new Window("end", WindowMode.Normal, open1 * 255);
            //Cv2.WaitKey();
            Scalar sum1 = new Scalar(0);
            Scalar lastSum1 = new Scalar(0);
            Scalar sub1 = new Scalar(0);
            Scalar subMax1 = new Scalar(0);
            Scalar max1 = new Scalar(0);
            Scalar zero1 = new Scalar(0);
            int y = 0;
            for (int i = crop1.Rows - 4; i > 4; i--)
            {
                sum1 = open1[i - 3, i, 0, open1.Cols].Sum();
                if ((int)sum1 > width1 * 2.9)
                {
                    y = i;
                    break;
                }
            }
            for (int i = y - 1; i > 4; i--)
            {
                sum1 = open1[i - 3, i, 0, open1.Cols].Sum();
                if ((int)sum1 < width1 * 2.2)
                {
                    glueOrdinate[0] = i + leftUpper;
                    break;
                }
            }
            //右
            Mat crop2 = image[rightUpper, rightLower, dataArea[2], dataArea[3]];
            int width2 = dataArea[3] - dataArea[2];
            if (width2 > 50)
            {
                crop2 = image[rightUpper, rightLower, dataArea[2] + (width2 - 50) / 2, dataArea[3] - (width2 - 50) / 2];
                width2 = crop2.Cols;
            }
            ////将裁剪区域改为面铜+基材铜附近
            //int rightMiddleMiantong_Jicaitong = (dataArea[2] + dataArea[3]) / 2;
            //Mat crop2 = image[rightUpper, rightLower, rightMiddleMiantong_Jicaitong - 10, rightMiddleMiantong_Jicaitong + 10];
            int areaSize2 = crop2.Rows * crop2.Cols;
            Mat filter2 = new Mat();
            Cv2.Filter2D(crop2, filter2, -1, kernel);
            Cv2.ConvertScaleAbs(filter2, filter2);
            Mat thresh2 = 1 - filter2.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat open2 = new Mat();
            Cv2.MorphologyEx(thresh2, open2, MorphTypes.Open, seOpen);
            Cv2.MorphologyEx(open2, open2, MorphTypes.Close, seOpen);
            Cv2.Dilate(open2, open2, seDilate);
            Fill(open2, out open2, 1);
            Scalar area2 = open2.Sum();
            while ((int)area2 > areaSize2 * 0.9)
            {
                rightUpper += 5;
                crop2 = image[rightUpper, rightLower, dataArea[2], dataArea[3]];
                width2 = dataArea[3] - dataArea[2];
                if (width2 > 50)
                {
                    crop2 = image[rightUpper, rightLower, dataArea[2] + (width2 - 50) / 2, dataArea[3] - (width2 - 50) / 2];
                    width2 = crop2.Cols;
                }
                areaSize2 = crop2.Rows * crop2.Cols;
                filter2 = new Mat();
                Cv2.Filter2D(crop2, filter2, -1, kernel);
                Cv2.ConvertScaleAbs(filter2, filter2);
                thresh2 = 1 - filter2.Threshold(0, 1, ThresholdTypes.Otsu);
                open2 = new Mat();
                Cv2.MorphologyEx(thresh2, open2, MorphTypes.Open, seOpen);
                Cv2.MorphologyEx(open2, open2, MorphTypes.Close, seOpen);
                Cv2.Dilate(open2, open2, seDilate);
                Fill(open2, out open2, 1);
                area2 = open2.Sum();
            }
            //new Window("crop2", WindowMode.Normal, crop2);
            //new Window("filter2", WindowMode.Normal, filter2);
            //new Window("thresh2", WindowMode.Normal, thresh2 * 255);
            //new Window("end2", WindowMode.Normal, open2 * 255);
            //Cv2.WaitKey();
            Scalar sum2 = new Scalar(0);
            Scalar lastSum2 = new Scalar(0);
            Scalar sub2 = new Scalar(0);
            Scalar subMax2 = new Scalar(0);
            Scalar max2 = new Scalar(0);
            Scalar zero2 = new Scalar(0);
            y = 0;
            for (int i = crop2.Rows - 4; i > 4; i--)
            {
                sum2 = open2[i - 3, i, 0, open2.Cols].Sum();
                if ((int)sum2 > width2 * 2.9)
                {
                    y = i;
                    break;
                }
            }
            for (int i = y - 1; i > 4; i--)
            {
                sum2 = open2[i - 3, i, 0, open2.Cols].Sum();
                if ((int)sum2 < width2 * 2.4)
                {
                    glueOrdinate[1] = i + rightUpper;
                    break;
                }
            }
            if (glueOrdinate[0] == 0)
                glueOrdinate[0] = leftUpper;
            if (glueOrdinate[1] == 0)
                glueOrdinate[1] = rightUpper;
        }
        /// <summary>
        /// 得到深盲孔胶内缩的内部坐标
        /// </summary>
        /// <param name="imageContour">二值图像</param>
        /// <param name="upperWaist">输出内部坐标，先左后右</param>
        /// <param name="lowerWaist">输出外部坐标，先左后右</param>
        /// <param name="upperBound">上界</param>
        /// <param name="glueOrdinate">胶线的坐标</param>
        /// <param name="lowerBound">下界</param>
        /// <param name="dataArea">提取数据区域</param>
        public void GetWaist(Mat imageContour, out int[] upperWaist, out int[] lowerWaist, int upperBound, int[] glueOrdinate, int lowerBound, int[] dataArea)
        {
            //Cv2.ImWrite(@"C:\Users\zyh\Desktop\imageContour.jpg", imageContour * 255);
            //寻找连通区域,把除第一个联通区域的都置为0
            Mat labelMat = new Mat();
            Mat stats = new Mat();
            Mat centroids = new Mat();
            int nums = Cv2.ConnectedComponentsWithStats(imageContour, labelMat, stats, centroids, PixelConnectivity.Connectivity8);
            int y = stats.At<int>(1, 1);
            int height = stats.At<int>(1, 3);
            for(int h=height+1; h< imageContour.Height; h++)
            {
                imageContour.Row[h] *= 0;
            }
            upperWaist = new int[2] { 0, 0 };
            lowerWaist = new int[2] { 0, 0 };
            int middle = (dataArea[1] + dataArea[2]) / 2;

            int min_left=int.MaxValue, max_left = 0;
            int min_left_x = 0, max_left_x = 0;
            for (int j = middle-30; j > dataArea[1]; j--)
            {
                int v = imageContour.Col[j].CountNonZero();
                if (v <= min_left) { min_left = v; min_left_x = j; }
                if (v >= max_left) { max_left = v; max_left_x = j; }
            }
            upperWaist[0] = max_left_x;
            OpenCvSharp.Rect rect_Left = new Rect(dataArea[1], upperBound, max_left_x- dataArea[1], lowerBound- upperBound);
            Mat temp_left = new Mat(imageContour, rect_Left);
            //Cv2.ImWrite(@"C:\Users\zyh\Desktop\temp_left.jpg", temp_left*255);
            bool f_l = false;
            for (int j=0; j< temp_left.Width; j++)
            {
                if(!f_l && temp_left.Col[j].CountNonZero()>0)
                {
                    f_l = true;
                    lowerWaist[0] = j + dataArea[1];
                    //break;
                }
                else if(temp_left.Col[j].CountNonZero()== temp_left.Height)
                {
                    upperWaist[0] = j + dataArea[1];
                    break;
                }
            }

            int min_right = int.MaxValue, max_right = 0;
            int min_right_x = 0, max_right_x = 0;
            for (int j = middle+30; j < dataArea[2]; j++)
            {
                int v = imageContour.Col[j].CountNonZero();
                if (v <= min_right) { min_right = v; min_right_x = j; }
                if (v >= max_right) { max_right = v; max_right_x = j; }
            }
            upperWaist[1] = max_right_x;
            OpenCvSharp.Rect rect_right = new Rect(max_right_x, upperBound, dataArea[2]- max_right_x, lowerBound - upperBound);
            Mat temp_right = new Mat(imageContour, rect_right);
            //Cv2.ImWrite(@"C:\Users\zyh\Desktop\rect_right.jpg", temp_right*255);
            bool f_r = false;
            for (int j = temp_right.Width-1; j > 0; j--)
            {
                if (!f_r && temp_right.Col[j].CountNonZero() > 0)
                {
                    f_r = true;
                    lowerWaist[1] = j+ max_right_x;
                    //break;
                }
                else if(temp_right.Col[j].CountNonZero() == temp_right.Height)
                {
                    upperWaist[1] = j + max_right_x;
                    break;
                }
            }

            /*Mat fanse = 1 - imageContour;
            //上
            for (int j = middle; j > dataArea[0]; j--)
            {
                for (int i = upperBound; i < glueOrdinate[0]; i++)
                {
                    if (fanse.Get<byte>(i, j) > 0*//* && j< (middle + dataArea[0]) / 2*//*)
                    {
                        upperWaist[0] = j;
                        break;
                    }
                }
                if (upperWaist[0] != 0)
                    break;
            }
            for (int j = middle; j < dataArea[3]; j++)
            {
                for (int i = upperBound; i < glueOrdinate[1]; i++)
                {
                    if (fanse.Get<byte>(i, j) > 0*//* && j > (middle + dataArea[3])/2*//*)
                    {
                        upperWaist[1] = j;
                        break;
                    }
                }
                if (upperWaist[1] != 0)
                    break;
            }
            //下
            for (int j = (dataArea[0] + dataArea[1]) / 2; j < middle; j++)
            {
                for (int i = glueOrdinate[0] - 20; i < lowerBound; i++)
                {
                    //new Window("imageContour", WindowMode.Normal, imageContour * 255);
                    //Cv2.WaitKey();
                    if (imageContour.Get<byte>(i, j) > 0)
                    {
                        lowerWaist[0] = j;
                        break;
                    }
                }
                if (lowerWaist[0] != 0)
                    break;
            }
            for (int j = (dataArea[3] + dataArea[2]) / 2; j > middle; j--)
            {
                for (int i = glueOrdinate[1] - 20; i < lowerBound; i++)
                {
                    if (imageContour.Get<byte>(i, j) > 0)
                    {
                        lowerWaist[1] = j;
                        break;
                    }
                }
                if (lowerWaist[1] != 0)
                    break;
            }*/

        }
        /// <summary>
        /// 提取胶内缩，将下边界改为左右边界
        /// </summary>
        /// <param name="imageContour">二值图像</param>
        /// <param name="upperWaist">输出内部坐标，先左后右</param>
        /// <param name="lowerWaist">输出外部坐标，先左后右</param>
        /// <param name="upperBound">上界</param>
        /// <param name="glueOrdinate">胶线的坐标</param>
        /// <param name="leftLower">下左界</param>
        /// <param name="rightLower">下右界</param>
        /// <param name="dataArea">提取数据区域</param>
        public void GetWaistNew(Mat imageContour, out int[] upperWaist, out int[] lowerWaist, int upperBound, int[] glueOrdinate, int leftLower, int rightLower, int[] dataArea)
        {
            upperWaist = new int[2] { 0, 0 };
            lowerWaist = new int[2] { 0, 0 };
            int middle = (dataArea[1] + dataArea[2]) / 2;
            Mat fanse = 1 - imageContour;
            //上
            for (int j = middle; j > dataArea[0]; j--)
            {
                for (int i = upperBound; i < glueOrdinate[0]; i++)
                {
                    if (fanse.Get<byte>(i, j) > 0)
                    {
                        upperWaist[0] = j;
                        break;
                    }
                }
                if (upperWaist[0] != 0)
                    break;
            }
            for (int j = middle; j < dataArea[3]; j++)
            {
                for (int i = upperBound; i < glueOrdinate[1]; i++)
                {
                    if (fanse.Get<byte>(i, j) > 0)
                    {
                        upperWaist[1] = j;
                        break;
                    }
                }
                if (upperWaist[1] != 0)
                    break;
            }
            //下
            //左
            for (int j = (dataArea[0] + dataArea[1]) / 2; j < middle; j++)
            {
                for (int i = glueOrdinate[0] - 20; i < leftLower; i++)
                {
                    //new Window("imageContour", WindowMode.Normal, imageContour * 255);
                    //Cv2.WaitKey();
                    if (imageContour.Get<byte>(i, j) > 0)
                    {
                        lowerWaist[0] = j;
                        break;
                    }
                }
                if (lowerWaist[0] != 0)
                    break;
            }
            //右
            for (int j = (dataArea[3] + dataArea[2]) / 2; j > middle; j--)
            {
                for (int i = glueOrdinate[1] - 20; i < rightLower; i++)
                {
                    if (imageContour.Get<byte>(i, j) > 0)
                    {
                        lowerWaist[1] = j;
                        break;
                    }
                }
                if (lowerWaist[1] != 0)
                    break;
            }

        }

        /// <summary>
        /// 得到精准的面铜和基材铜的纵坐标
        /// </summary>
        /// <param name="image">最好是绿色通道图</param>
        /// <param name="upperBound">上边界</param>
        /// <param name="lowerBound">下边界</param>
        /// <param name="leftBoundary">左边界</param>
        /// <param name="rightBoundary">右边界</param>
        /// <param name="middleMiantong">面铜的横坐标</param>
        /// <param name="middleJicaitong">基材铜的横坐标</param>
        /// <param name="ordinateL2Miantong">面铜的纵坐标</param>
        /// <param name="ordinateL2Jicaitong">基材铜的纵坐标</param>
        /// <param name="ordinateL2_Acc">输出纵坐标，面铜和基材铜</param>
        public void InsideLine_Accuracy(Mat image, int upperBound, int lowerBound, int leftBoundary, int rightBoundary, int middleMiantong, int middleJicaitong
            , double ordinateL2Miantong, double ordinateL2Jicaitong, out double[] ordinateL2_Acc, int isMiantong = 0, int banceng = 2/*-1*/, bool showMat = false)
        {
            //第5671deng类别图片需要完善位置精准度，以及 调试有些图片位置计算错误的原因，并纠正
            Mat crop = image[upperBound, lowerBound, leftBoundary, rightBoundary];
            //if (isMiantong > 0 && showMat)
            //{
            //    Mat mat1 = new Mat();
            //    Cv2.Normalize(crop, mat1, 0, 255, NormTypes.MinMax);
            //    Cv2.ImWrite(@"C:\Users\54434\Desktop\crop.JPG", crop);
            //}
            Mat filter = new Mat();//滤波增强对比
            InputArray kernel = InputArray.Create<int>(new int[3, 3] { { 0, -1, 0 }, { -1, 5, -1 }, { 0, -1, 0 } });
            Cv2.Filter2D(crop, filter, -1, kernel);
            Cv2.ConvertScaleAbs(filter, filter);
            Mat thresh = 1 - filter.Threshold(0, 1, ThresholdTypes.Otsu);// 二值化
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(15/*15*/, 1/*水平线<--3, 3*/));// 开运算
            Mat open = new Mat();
            //OpenCV提取图像中的垂直线（或者水平线） 定义结构元素，开操作
            Cv2.MorphologyEx(thresh, open, MorphTypes.Open, seOpen);
            if (isMiantong > 0 && showMat)
            {
                //Cv2.ImWrite(@"C:\Users\54434\Desktop\filter.JPG", filter/* * 127*/);
            }
            //Scalar sum = new Scalar(0);
            //Scalar max1 = new Scalar(0);
            //Scalar max = new Scalar(0);
            //double meanOrdinate1 = 0;
            double ordinateL2Miantong_acc = ordinateL2Miantong;
            double ordinateL2Jicaitong_acc = ordinateL2Jicaitong;
            //ordinateL2_Acc = new double[] { ordinateL2Miantong_acc, ordinateL2Jicaitong_acc };
            //return;
            int topOri = (int)ordinateL2Miantong_acc - upperBound - 20;// 10;// 15;
            int bottomOri = (int)ordinateL2Miantong_acc - upperBound + 20;// 10;// 15;
            if (topOri < 10) topOri = 10;
            else if (topOri > crop.Rows/3 && topOri > 20) topOri = 20;//对初判定位置距离太远的进行纠偏
            if (bottomOri > crop.Rows - 10) bottomOri = crop.Rows - 10;
            else if (bottomOri < crop.Rows*2/3 && bottomOri < crop.Rows - 20) bottomOri = crop.Rows - 20;//对初判定位置距离太远的进行纠偏

            bool miantongChanged = false;
            int miantongValue = crop.Get<byte>((int)ordinateL2Miantong - upperBound, middleMiantong - leftBoundary);
            bool isHoriMost = false;//用来判定大横线哪个更加位置居中
            int centerVer = crop.Rows / 2;// (topOri + bottomOri) / 2;//用来判定大横线哪个更加位置居中
            for (int i = topOri; i < bottomOri; i++)
            {
                int miantongValueI = crop.Get<byte>(i, middleMiantong - leftBoundary);
                Scalar sum = open[i, i + 1, 0, crop.Cols - 1].Sum();
                if (miantongValueI < miantongValue - 1 || (!miantongChanged && miantongValueI < miantongValue + 100)
                    || crop.Cols - 20 < (int)sum)
                {
                    //if (open.Get<byte>(i, middleMiantong - leftBoundary) > 0)
                    //Scalar sum = open[i, i + 2, 0, crop.Cols - 1].Sum();
                    //if (30/*30*/ < (int)sum)
                    if (6/*30*/ < (int)sum && !isHoriMost
                        ||(crop.Cols - 20 < (int)sum && isHoriMost && Math.Abs(centerVer - i) < Math.Abs(centerVer - (ordinateL2Miantong_acc - upperBound))))
                    {
                        ordinateL2Miantong_acc = i + upperBound;
                        miantongValue = miantongValueI;
                        miantongChanged = true;
                        //待自测scc-2
                        //if (isMiantong == 1)
                        //    break;
                        if (crop.Cols - 20 < (int)sum/* && Math.Abs(centerVer - (ordinateL2Jicaitong_acc - upperBound)) < 10*/)
                        {
                            isHoriMost = true;
                            //break;
                        }
                    }
                }
            }
            if (ordinateL2Miantong_acc == 10 + upperBound)
            {//将明显不对的测量结果居中取值
                ordinateL2Miantong_acc = centerVer + upperBound;
            }

            //if (isMiantong == 1 && !miantongChanged)
            //{

            //    Mat thresh1 = 1 - filter.Threshold(0, 1, ThresholdTypes.Otsu);// 二值化
            //    Mat seOpen1 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(9/*15*/, 1/*水平线<--3, 3*/));// 开运算
            //    Mat open1 = new Mat();
            //    //OpenCV提取图像中的垂直线（或者水平线） 定义结构元素，开操作
            //    Cv2.MorphologyEx(thresh1, open1, MorphTypes.Open, seOpen1);
            //    //if (isMiantong > 0 && showMat)
            //    //{
            //    //    new Window("open1", WindowMode.Normal, open1 * 255);
            //    //    Cv2.WaitKey();
            //    //}
            //    for (int i = topOri; i < bottomOri; i++)
            //    {
            //        //int miantongValueI = crop.Get<byte>(i, middleMiantong - leftBoundary);
            //        //if (miantongValueI < 200/*miantongValue*/)
            //        {
            //            if (open1.Get<byte>(i, middleMiantong - leftBoundary) > 0)
            //            //Scalar sum = open[i, i + 2, 0, crop.Cols - 1].Sum();
            //            //if (30/*30*/ < (int)sum)
            //            {
            //                ordinateL2Miantong_acc = i + upperBound;
            //                miantongValue = crop.Get<byte>(i, middleMiantong - leftBoundary);// miantongValueI;
            //                miantongChanged = true;
            //                break;
            //            }
            //        }
            //    }
            //}

            isHoriMost = false;//用来判定大横线哪个更加位置居中

            bool jicaitongChanged = false;
            int jicaitongValue = crop.Get<byte>((int)ordinateL2Jicaitong - upperBound, middleJicaitong - leftBoundary);
            for (int i = /*0*/topOri; i < bottomOri; i++)
            {
                int jicaitongValueI = crop.Get<byte>(i, middleJicaitong - leftBoundary);
                Scalar sum = open[i, i + 1, 0, crop.Cols - 1].Sum();
                if (jicaitongValueI < jicaitongValue - 1 || (!jicaitongChanged && jicaitongValueI < jicaitongValue + 100)
                    || crop.Cols - 20 < (int)sum)
                {
                    //if (open.Get<byte>(i, middleJicaitong - leftBoundary) > 0)
                    //Scalar sum = open[i, i + 2, 0, crop.Cols - 1].Sum();
                    ////Scalar sum = open[i, i + 2, middleJicaitong - leftBoundary - 4, middleJicaitong - leftBoundary + 4].Sum();
                    if (6/*30*/ < (int)sum && !isHoriMost
                        || (crop.Cols - 20 < (int)sum && isHoriMost && Math.Abs(centerVer - i) < Math.Abs(centerVer - (ordinateL2Jicaitong_acc - upperBound))))
                    {
                        ordinateL2Jicaitong_acc = i + upperBound;
                        jicaitongValue = jicaitongValueI;
                        jicaitongChanged = true;
                        //待自测scc-2
                        //if (isMiantong == 1)
                        //    break;
                        if (crop.Cols - 20 < (int)sum/* && Math.Abs(centerVer - (ordinateL2Jicaitong_acc - upperBound)) < 10*/)
                        {
                            isHoriMost = true;
                            //break;
                        }
                    }
                }
            }
            if (ordinateL2Jicaitong_acc == 10 + upperBound)
            {//将明显不对的测量结果居中取值
                ordinateL2Jicaitong_acc = centerVer + upperBound;
            }

            if (!miantongChanged && !jicaitongChanged)
            {
                int topOri_1 = topOri;
                if (topOri > 10) topOri_1 = 10;
                int bottomOri_1 = bottomOri;
                if (bottomOri < crop.Rows - 10) bottomOri_1 = crop.Rows - 10;
                miantongValue = crop.Get<byte>((int)ordinateL2Miantong - upperBound, middleMiantong - leftBoundary);
                for (int i = topOri_1; i < bottomOri_1; i++)
                {
                    int miantongValueI = crop.Get<byte>(i, middleMiantong - leftBoundary);
                    Scalar sum = open[i, i + 1, 0, crop.Cols - 1].Sum();
                    if (miantongValueI < miantongValue - 1 || (!miantongChanged && miantongValueI < miantongValue + 100)
                        || crop.Cols - 20 < (int)sum)
                    {
                        if (6 < (int)sum)
                        {
                            ordinateL2Miantong_acc = i + upperBound;
                            miantongValue = miantongValueI;
                            miantongChanged = true;
                            if (crop.Cols - 20 < (int)sum)
                                break;
                        }
                    }
                    if (i == topOri - 1) i = bottomOri;
                }

                jicaitongValue = crop.Get<byte>((int)ordinateL2Jicaitong - upperBound, middleJicaitong - leftBoundary);
                for (int i = topOri_1; i < bottomOri_1; i++)
                {
                    int jicaitongValueI = crop.Get<byte>(i, middleJicaitong - leftBoundary);
                    Scalar sum = open[i, i + 1, 0, crop.Cols - 1].Sum();
                    if (jicaitongValueI < jicaitongValue - 1 || (!jicaitongChanged && jicaitongValueI < jicaitongValue + 100)
                        || crop.Cols - 20 < (int)sum)
                    {
                        if (6 < (int)sum)
                        {
                            ordinateL2Jicaitong_acc = i + upperBound;
                            jicaitongValue = jicaitongValueI;
                            jicaitongChanged = true;
                            if (crop.Cols - 20 < (int)sum)
                                break;
                        }
                    }
                    if (i == topOri - 1) i = bottomOri;
                }

            }


            if ((isMiantong == 1 || isMiantong == 2) && (!miantongChanged /*//待自测scc-3_1 &&*/|| !jicaitongChanged))
            {
                Mat thresh1 = 1 - filter.Threshold(0, 1, ThresholdTypes.Otsu);// 二值化
                Mat seOpen1 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(9/*15*/, 1/*水平线<--3, 3*/));// 开运算
                Mat open1 = new Mat();
                //OpenCV提取图像中的垂直线（或者水平线） 定义结构元素，开操作
                Cv2.MorphologyEx(thresh1, open1, MorphTypes.Open, seOpen1);
                //if (isMiantong > 0 && showMat)
                //{
                //    new Window("open1", WindowMode.Normal, open1 * 255);
                //    Cv2.WaitKey();
                //}
                
                
                
                //待自测scc-3_1
                if (isMiantong == 1 && !miantongChanged || isMiantong == 2 && !jicaitongChanged)
                    for (int i = bottomOri; i > topOri; i--)
                {
                        //还差第3、5、7类别图片需要完善位置精准度，以及
                        //调试有些图片位置计算错误的原因，并纠正！！！！！！！！！！！！
                    {
                        if (isMiantong == 1 && open1.Get<byte>(i, middleMiantong - leftBoundary) > 0
                            || isMiantong == 2 && open1.Get<byte>(i, middleJicaitong - leftBoundary) > 0)
                        {
                            if (isMiantong == 1)
                                ordinateL2Miantong_acc = i + upperBound;
                            else if (isMiantong == 2)
                                ordinateL2Jicaitong_acc = i + upperBound;
                            break;
                        }
                    }
                    }

                //if (isMiantong == 1 && !miantongChanged)
                //    for (int i = topOri; i < bottomOri; i++)//for (int i = bottomOri; i > topOri; i--)
                //    {
                //        if (open1.Get<byte>(i, middleMiantong - leftBoundary) > 0)
                //        {
                //            ordinateL2Miantong_acc = i + upperBound;
                //            break;
                //        }
                //    }
                //if (isMiantong == 2 && !jicaitongChanged)
                //    for (int i = bottomOri; i > topOri; i--)
                //    {
                //        if (open1.Get<byte>(i, middleJicaitong - leftBoundary) > 0)
                //        {
                //            ordinateL2Jicaitong_acc = i + upperBound;
                //            break;
                //        }
                //    }
                //if (isMiantong == 1 && !jicaitongChanged)
                //    for (int i = topOri; i < bottomOri; i++)
                //    {
                //        {
                //            if (open1.Get<byte>(i, middleJicaitong - leftBoundary) > 0)
                //            {
                //                ordinateL2Jicaitong_acc = i + upperBound;
                //                break;
                //            }
                //        }
                //    }
                //if (isMiantong == 2 && !miantongChanged)
                //    for (int i = bottomOri; i > topOri; i--)//for (int i = topOri; i < bottomOri; i++)
                //    {
                //        {
                //            if (open1.Get<byte>(i, middleMiantong - leftBoundary) > 0)
                //            {
                //                ordinateL2Miantong_acc = i + upperBound;
                //                break;
                //            }
                //        }
                //    }

                if (isMiantong == 1 && !jicaitongChanged || isMiantong == 2 && !miantongChanged)
                    for (int i = topOri; i < bottomOri; i++)
                {
                    {
                        if (isMiantong == 1 && open1.Get<byte>(i, middleJicaitong - leftBoundary) > 0
                            || isMiantong == 2 && open1.Get<byte>(i, middleMiantong - leftBoundary) > 0)
                        {
                            if (isMiantong == 1)
                                ordinateL2Jicaitong_acc = i + upperBound;
                            else if (isMiantong == 2)
                                ordinateL2Miantong_acc = i + upperBound;
                            break;
                        }
                    }
                }
            }

            //if (isMiantong == 1 && !jicaitongChanged)
            //{

            //    Mat thresh1 = 1 - filter.Threshold(0, 1, ThresholdTypes.Otsu);// 二值化
            //    Mat seOpen1 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(9/*15*/, 1/*水平线<--3, 3*/));// 开运算
            //    Mat open1 = new Mat();
            //    //OpenCV提取图像中的垂直线（或者水平线） 定义结构元素，开操作
            //    Cv2.MorphologyEx(thresh1, open1, MorphTypes.Open, seOpen1);
            //    //if (isMiantong > 0 && showMat)
            //    //{
            //    //    new Window("open1", WindowMode.Normal, open1 * 255);
            //    //    Cv2.WaitKey();
            //    //}
            //    for (int i = bottomOri; i > topOri; i--)
            //    {
            //        //int miantongValueI = crop.Get<byte>(i, middleMiantong - leftBoundary);
            //        //if (miantongValueI < 200/*miantongValue*/)
            //        {
            //            if (open1.Get<byte>(i, middleJicaitong - leftBoundary) > 0)
            //            //Scalar sum = open[i, i + 2, 0, crop.Cols - 1].Sum();
            //            //if (30/*30*/ < (int)sum)
            //            {
            //                ordinateL2Jicaitong_acc = i + upperBound;
            //                jicaitongValue = crop.Get<byte>(i, middleJicaitong - leftBoundary);// miantongValueI;
            //                jicaitongChanged = true;
            //                break;
            //            }
            //        }
            //    }
            //}
            ////if (isMiantong == 1 && jicaitongChanged && showMat)
            ////{

            ////    Mat thresh1 = 1 - filter.Threshold(0, 1, ThresholdTypes.Otsu);// 二值化
            ////    //Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(11/*15*/, 1/*水平线<--3, 3*/));// 开运算
            ////    //Mat open = new Mat();
            ////    ////OpenCV提取图像中的垂直线（或者水平线） 定义结构元素，开操作
            ////    //Cv2.MorphologyEx(thresh, open, MorphTypes.Open, seOpen);
            ////    ////if (isMiantong > 0 && showMat)
            ////    ////{
            ////    ////    new Window("open", WindowMode.Normal, open * 255);
            ////    ////    Cv2.WaitKey();
            ////    ////}
            ////}

            ordinateL2_Acc = new double[] { ordinateL2Miantong_acc, ordinateL2Jicaitong_acc };
        }

        /// <summary>
        /// 得到内部线纵坐标
        /// </summary>
        /// <param name="image">最好是绿色通道图</param>
        /// <param name="upperBound">上边界</param>
        /// <param name="lowerBound">下边界</param>
        /// <param name="leftBoundary">左边界</param>
        /// <param name="rightBoundary">右边界</param>
        /// <param name="meanOrdinate">输出坐标</param>
        public double InsideLine(Mat image, int upperBound, int lowerBound, int leftBoundary, int rightBoundary, out double meanOrdinate
            , int isMiantong = 0, bool showMat = false)
        {
            Mat crop = image[upperBound, lowerBound, leftBoundary-10, rightBoundary+10];
            
            /*int pos = -1;
            int min = int.MaxValue;
            for(int i=0; i< crop.Height-5; i++)
            {
                int sum = (int)(crop.Row[i].Sum())+ (int)(crop.Row[i+1].Sum())+ (int)(crop.Row[i+2].Sum())
                    + (int)(crop.Row[i+3].Sum())+ (int)(crop.Row[i+4].Sum());
                if (sum < min)
                {
                    pos = i;
                    min = sum;
                }
            }

            if((int)(image.Row[pos+ upperBound].Sum()) < (int)(image.Row[pos+ upperBound + 40].Sum()) && pos< crop.Height/2)
            {
                int start = pos + 10;
                pos = -1;
                min = int.MaxValue;
                for (int i = start; i < crop.Height; i++)
                {
                    int sum = (int)(crop.Row[i].Sum());
                    if (sum < min)
                    {
                        pos = i;
                        min = sum;
                    }
                }
            }

            meanOrdinate = pos + upperBound;
            return meanOrdinate;*/


            Mat filter = new Mat();//滤波增强对比
            InputArray kernel = InputArray.Create<int>(new int[3, 3] { { 0, -1, 0 }, { -1, 5, -1 }, { 0, -1, 0 } });
            Cv2.Filter2D(crop, filter, -1, kernel);
            Cv2.ConvertScaleAbs(filter, filter);
            Mat thresh = 1 - filter.Threshold(0, 1, ThresholdTypes.Otsu); ;// 二值化
            //待自测scc-3_2 //此处针对3(4)的类型图片做精准化调整
            //int sizeSe = 3; if (isMiantong == 2) sizeSe = 1;// 3;// 1;
            //Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, sizeSe/*3*/));// 开运算
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));// 开运算
            Mat open = new Mat();
            Cv2.MorphologyEx(thresh, open, MorphTypes.Open, seOpen);

            //if (isMiantong > 0 && showMat)
            //{
            //    Mat mat1 = new Mat();
            //    Cv2.Normalize(open, mat1, 0, 255, NormTypes.MinMax);
            //    Cv2.ImWrite(@"C:\Users\54434\Desktop\open.JPG", mat1);
            //}

            Scalar sum = new Scalar(0);
            Scalar max1 = new Scalar(0);
            Scalar max = new Scalar(0);
            double meanOrdinate1 = 0;
            meanOrdinate = 0;//待自测scc-3_2 + upperBound;
            for (int i = crop.Rows / 4; i < crop.Rows / 4 * 3; i++)
            {
                sum = open[i, i + 2, 0, crop.Cols - 1].Sum();
                if ((int)max < (int)sum)
                {
                    if (isMiantong > 0 && i + upperBound > 10 + meanOrdinate)
                    {
                        max1 = max;
                        meanOrdinate1 = meanOrdinate;
                    }
                    max = sum;
                    meanOrdinate = i + upperBound;
                }
                else if (isMiantong > 0 && i + upperBound > 10 + meanOrdinate && (int)max1 < (int)sum)
                {
                    max1 = sum;
                    meanOrdinate1 = i + upperBound;
                }
            }
            if (isMiantong > 0)
            {
                if (meanOrdinate < meanOrdinate1 && isMiantong == 1
                    || meanOrdinate > meanOrdinate1 && meanOrdinate1 > 0 && isMiantong == 2
                    )
                {
                    double meanOrdinate_i = meanOrdinate;
                    meanOrdinate = meanOrdinate1;
                    meanOrdinate1 = meanOrdinate_i;
                }
            }
            //待自测scc-3_2
            //if (meanOrdinate == upperBound)
            //    meanOrdinate = meanOrdinate1;

            //尝试纠偏一下，可是还有差很亮的，可能还是需要二值 待确认@@@@@@@@@@@@@
            if ((int)(image.Row[(int)meanOrdinate].Sum()) < (int)(image.Row[Math.Min(image.Rows - 1, (int)meanOrdinate + 40)].Sum())-100000 && (meanOrdinate- upperBound) < crop.Height / 2
                && ((int)crop.Row[(int)meanOrdinate - upperBound + 10].Sum() - (int)crop.Row[(int)meanOrdinate - upperBound - 10].Sum()) < crop.Width*25)
            {
                int start = (int)(meanOrdinate - upperBound + 10);
                int pos = -1;
                int min = int.MaxValue;
                for (int i = start; i < crop.Height; i++)
                {
                    int sum_a = (int)(crop.Row[i].Sum());
                    if (sum_a < min)
                    {
                        pos = i;
                        min = sum_a;
                    }
                }

                meanOrdinate = pos + upperBound;
            }

            #region[清理内存]
            if (crop != null)
            {
                crop.Dispose();
            }
            if (open != null)
            {
                open.Dispose();
            }
            if (filter != null)
            {
                filter.Dispose();
            }

            if (thresh != null)
            {
                thresh.Dispose();
            }
            if (seOpen != null)
            {
                seOpen.Dispose();
            }
          
            #endregion
            return meanOrdinate1;
        }
        /// <summary>
        /// 將計算的範圍從整個行數變成四分之一到四分之三之間，不知道通孔和盲孔改變之後會不會有影響，暫時沒引用
        /// </summary>
        /// <param name="image"></param>
        /// <param name="upperBound"></param>
        /// <param name="lowerBound"></param>
        /// <param name="leftBoundary"></param>
        /// <param name="rightBoundary"></param>
        /// <param name="meanOrdinate"></param>
        public void InsideLine2(Mat image, int upperBound, int lowerBound, int leftBoundary, int rightBoundary, out double meanOrdinate)
        {
            Mat crop = image[upperBound, lowerBound, leftBoundary, rightBoundary];
            Mat filter = new Mat();//滤波增强对比
            InputArray kernel = InputArray.Create<int>(new int[3, 3] { { 0, -1, 0 }, { -1, 5, -1 }, { 0, -1, 0 } });
            Cv2.Filter2D(crop, filter, -1, kernel);
            Cv2.ConvertScaleAbs(filter, filter);
            Mat thresh = 1 - filter.Threshold(0, 1, ThresholdTypes.Otsu); ;// 二值化            
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));// 开运算
            Mat open = new Mat();
            Cv2.MorphologyEx(thresh, open, MorphTypes.Open, seOpen);
            //new Window("thresh", WindowMode.Normal, thresh * 255);
            //new Window("open", WindowMode.Normal, open * 255);
            //Cv2.WaitKey();
            Scalar sum = new Scalar(0);
            Scalar max = new Scalar(0);
            meanOrdinate = 0;
            for (int i = crop.Rows / 4; i < crop.Rows / 4 * 3; i++)
            {
                sum = open[i, i + 2, 0, crop.Cols - 1].Sum();
                if ((int)max < (int)sum)
                {
                    max = sum;
                    meanOrdinate = i + upperBound;
                }
            }
        }
        /// <summary>
        /// 图像画线，线颜色是红色
        /// </summary>
        /// <param name="image">画线图像</param>
        /// <param name="x1"></param>
        /// <param name="y1"></param>
        /// <param name="x2"></param>
        /// <param name="y2"></param>

        /// <summary>
        /// 计算盲孔的上孔径
        /// </summary>
        /// <param name="image">输入二值图片</param>
        /// <param name="apertureLow">输入下孔径</param>
        /// <param name="leftOrdinate3">左边第三条线坐标</param>
        /// <param name="rightOrdinate3">右边第三条线坐标</param>
        /// <param name="leftAperture">输出左边孔径坐标，先纵坐标后横坐标</param>
        /// <param name="rightAperture">输出右边孔径坐标，先纵坐标后横坐标</param>
        public void ShangKongjing(/*Mat imageRed, */Mat image, int[] apertureLow, int leftOrdinate3, int rightOrdinate3, out int[] leftAperture, out int[] rightAperture)
        {
            leftAperture = new int[2] { 0, 0 };
            rightAperture = new int[2] { 0, 0 };
            int heightRange = 15;
            int widthMiddleRange = 1;
            int widthRange = 200;
            Mat cropLeft = 1 - image[leftOrdinate3 - heightRange, leftOrdinate3 + heightRange, Math.Abs(apertureLow[0] - widthRange), apertureLow[0] + widthMiddleRange];
            //Mat crop = imageRed[leftOrdinate3 - 15, leftOrdinate3 + 15, apertureLow[0] - 50, apertureLow[0] + 10];
            Mat cropRight = 1 - image[rightOrdinate3 - heightRange, rightOrdinate3 + heightRange, apertureLow[1] - widthMiddleRange, apertureLow[1] + widthRange];
            for (int j = cropLeft.Cols - 1; j > 0; j--)//从右上角，以135°方向遍历
            {
                for (int k = j; k < cropLeft.Cols && (k - j < cropLeft.Rows); k++)
                {
                    if (cropLeft.Get<byte>(k - j, k) > 0)
                    {
                        leftAperture[0] = k - j + leftOrdinate3 - heightRange;
                        leftAperture[1] = k + apertureLow[0] - widthRange;
                        //LineShow(crop, new Point(k, k - j), new Point(k, k - j + 10));
                        //new Window("cropleft", WindowMode.Normal, crop);
                        //Cv2.WaitKey();
                        break;

                    }
                }
                if (leftAperture[0] != 0)
                    break;
            }
            if (leftAperture[0] == 0)
            {
                for (int j = 1; j < cropLeft.Rows; j++)
                {
                    for (int k = 0; k < cropLeft.Rows - j - 1; k++)
                    {
                        if (cropLeft.Get<byte>(j + k, k) > 0)
                        {
                            leftAperture[0] = j + k + leftOrdinate3 - heightRange;
                            leftAperture[1] = k + apertureLow[0] - widthRange;
                            break;
                        }
                    }
                    if (leftAperture[0] != 0)
                        break;
                }
            }

            for (int j = 0; j < cropRight.Cols; j++)//从左上角，45°方向遍历
            {
                for (int k = j; k >= 0 && j - k < cropRight.Rows; k--)
                {
                    if (cropRight.Get<byte>(j - k, k) > 0)
                    {
                        rightAperture[0] = j - k + rightOrdinate3 - heightRange;
                        rightAperture[1] = k + apertureLow[1] - widthMiddleRange;
                        break;
                    }
                }
                if (rightAperture[0] != 0)
                    break;
            }
            if (rightAperture[0] == 0)
            {
                for (int j = 1; j < cropRight.Rows; j++)
                {
                    for (int k = cropRight.Cols - 1; cropRight.Cols - 1 - k < cropRight.Rows - j - 1; k--)
                    {
                        if (cropRight.Get<byte>(j + cropRight.Cols - 1 - k, k) > 0)
                        {
                            rightAperture[0] = j + cropRight.Cols - 1 - k + rightOrdinate3 - heightRange;
                            rightAperture[1] = k + apertureLow[1] - widthMiddleRange;
                            break;
                        }
                    }
                    if (rightAperture[0] != 0)
                        break;
                }
            }
            //new Window("cropleft", WindowMode.Normal, cropLeft * 255);
            //new Window("cropRight", WindowMode.Normal, cropRight * 255);
            //Cv2.WaitKey();
        }
        /// <summary>
        /// 计算盲孔的上孔径,修改了计算方法，通过孔径不为零坐标和的最小值来定位
        /// </summary>
        /// <param name="image">输入二值图片</param>
        /// <param name="apertureLow">输入下孔径</param>
        /// <param name="leftOrdinate3">左边第三条线坐标</param>
        /// <param name="rightOrdinate3">右边第三条线坐标</param>
        /// <param name="leftAperture">输出左边孔径坐标，先纵坐标后横坐标</param>
        /// <param name="rightAperture">输出右边孔径坐标，先纵坐标后横坐标</param>
        public void ShangKongjing2(Mat image, int[] apertureLow, int leftOrdinate3, int rightOrdinate3, out int[] leftAperture, out int[] rightAperture)
        {
            leftAperture = new int[2] { 0, 0 };
            rightAperture = new int[2] { 0, 0 };
            int heightRange = 10;
            int widthMiddleRange = 50;
            int widthRange = 200;
            Mat cropLeft = 1 - image[leftOrdinate3 - heightRange, leftOrdinate3 + heightRange, apertureLow[0] - widthRange, apertureLow[0] + widthMiddleRange];
            //Mat crop = imageRed[leftOrdinate3 - 15, leftOrdinate3 + 15, apertureLow[0] - 50, apertureLow[0] + 10];
            Mat cropRight = 1 - image[rightOrdinate3 - heightRange, rightOrdinate3 + heightRange, apertureLow[1] - widthMiddleRange, apertureLow[1] + widthRange];
            Cv2.Flip(cropLeft, cropLeft, FlipMode.Y);
            int minLeft = 1000, minRight = 1000;
            int t1 = 0, t2 = 0;
            for (int i = 0; i < cropLeft.Rows; i++)
            {
                for (int j = 0; j < cropLeft.Cols; j++)
                {
                    if (cropLeft.Get<byte>(i, j) > 0)
                    {
                        t1 = i + j;
                    }
                    if (minLeft > t1 + 10 && t1 != 0)
                    {
                        minLeft = t1;
                        leftAperture[0] = i + leftOrdinate3 - heightRange;
                        leftAperture[1] = cropLeft.Cols - j + apertureLow[0] - widthRange;
                    }
                }
            }
            for (int i = 0; i < cropRight.Rows; i++)
            {
                for (int j = 0; j < cropRight.Cols; j++)
                {
                    if (cropRight.Get<byte>(i, j) > 0)
                    {
                        t2 = i + j;
                    }
                    if (minRight > t2 && t2 != 0)
                    {
                        minRight = t2;
                        rightAperture[0] = i + rightOrdinate3 - heightRange;
                        rightAperture[1] = j + apertureLow[1] - widthMiddleRange;
                    }
                }
            }
            //new Window("cropcontour", WindowMode.Normal, image * 255);
            new Window("cropleft", WindowMode.Normal, cropLeft * 255);
            //new Window("cropright", WindowMode.Normal, cropRight * 255);
            Cv2.WaitKey();
        }
        //蝕刻因子

        /// <summary>
        /// 得到蝕刻因子圖像的提取區域
        /// </summary>
        /// <param name="imageContour">輸入二值圖像</param>
        /// <param name="dataArea">輸出邊界位置，0：上界；1：下界；2：左界；3：右界</param>
        public void SKYZDataArea(Mat imageContour, out int[] dataArea, bool isCropFlag)
        {
            dataArea = new int[4] { 0, 0, 0, 0 };
            Scalar sum = new Scalar();
            for (int i = 100; i < imageContour.Rows; i++)
            {
                sum = imageContour[i, i + 1, 0, imageContour.Cols].Sum();
                if ((int)sum > 0)
                {
                    dataArea[0] = i;//上界
                    break;
                }
            }
            for (int i = dataArea[0]; i < imageContour.Rows; i++)
            {
                sum = imageContour[i, i + 1, 0, imageContour.Cols].Sum();
                if ((int)sum == 0)
                {
                    dataArea[1] = i;//下界
                    break;
                }
            }
            if (isCropFlag)
            {
                for (int j = 0; j < imageContour.Cols - 1; j++)
                {
                    sum = imageContour[dataArea[0], dataArea[1], j, j + 1].Sum();
                    if ((int)sum > 0)
                    {
                        dataArea[2] = j;
                        break;
                    }
                }
                for (int j = imageContour.Cols - 1; j > 1; j--)
                {
                    sum = imageContour[dataArea[0], dataArea[1], j - 1, j].Sum();
                    {
                        if ((int)sum > 0)
                        {
                            dataArea[3] = j;
                            break;
                        }
                    }
                }
            }
            else
            {
                int t = 0;
                for (int j = imageContour.Cols - 100; j > 0; j--)
                {
                    sum = imageContour[dataArea[0], dataArea[1], j - 1, j].Sum();
                    if ((int)sum > 0)
                    {
                        t = j;//最右邊的開始
                        break;
                    }
                }
                for (int j = t - 1; j > 0; j--)
                {
                    sum = imageContour[dataArea[0], dataArea[1], j - 1, j].Sum();
                    if ((int)sum == 0)
                    {
                        t = j;//最右邊的結束
                        break;
                    }
                }
                for (int j = t - 1; j > 0; j--)
                {
                    sum = imageContour[dataArea[0], dataArea[1], j - 1, j].Sum();
                    if ((int)sum > 0)
                    {
                        t = j;//中間開始
                        dataArea[3] = j;
                        break;
                    }
                }
                for (int j = t - 1; j > 0; j--)
                {
                    sum = imageContour[dataArea[0], dataArea[1], j - 1, j].Sum();
                    if ((int)sum == 0)
                    {
                        t = j;//中間結束
                        dataArea[2] = j;
                        break;
                    }
                }
            }
        }
        /// <summary>
        /// 提取上幅的值及坐標
        /// </summary>
        /// <param name="imageContour">輸入二值圖像</param>
        /// <param name="upperLineValue">上幅的大小</param>
        /// <param name="upperLineOrdinate">上幅的坐標，0：縱坐標；1：左橫坐標；2：右橫坐標</param>
        public void UpperLine(Mat imageContour, out int upperLineValue, out int[] upperLineOrdinate)
        {
            upperLineValue = 0;
            upperLineOrdinate = new int[3] { 0, 0, 0 };
            int cols = imageContour.Cols;
            int rows = imageContour.Rows;
            Scalar sum = new Scalar();
            for (int i = 0; i < rows - 150; i++)
            {
                sum = imageContour[i, i + 1, 0, cols].Sum();
                if ((int)sum > cols * 5 / 6)//儅每行點數大於寬度的五分之四時，判爲上幅
                {
                    upperLineOrdinate[0] = i;
                    break;
                }
            }
            if (upperLineOrdinate[0] == 0)//如果没有检测到
            {
                for (int i = 0; i < rows / 4; i++)
                {
                    sum = imageContour[i, i + 1, 0, cols].Sum();
                    if ((int)sum > cols * 4 / 5)//儅每行點數大於寬度的五分之三時，判爲上幅
                    {
                        upperLineOrdinate[0] = i;
                        break;
                    }
                }
            }
            int max = 0;
            int t = upperLineOrdinate[0];
            //繼續向下10（5）個像素尋找最大行，并認爲是上幅
            for (int i = t; i < t + 10; i++)
            {
                sum = imageContour[i, i + 1, 0, cols].Sum();
                if ((int)sum > max)
                {
                    max = (int)sum;
                    upperLineOrdinate[0] = i;
                }
            }
            //左邊點坐標
            for (int j = 0; j < cols; j++)
            {
                if (imageContour.Get<byte>(upperLineOrdinate[0], j) > 0)
                {
                    upperLineOrdinate[1] = j;
                    break;
                }
            }
            //右邊點坐標
            for (int j = cols - 1; j > 0; j--)
            {
                if (imageContour.Get<byte>(upperLineOrdinate[0], j) > 0)
                {
                    upperLineOrdinate[2] = j;
                    break;
                }
            }
            upperLineValue = upperLineOrdinate[2] - upperLineOrdinate[1];
        }
        public void UpperLine2(Mat imageContour, out int upperLineValue, out int[] upperLineOrdinate)
        {
            upperLineValue = 0;
            upperLineOrdinate = new int[3] { 0, 0, 0 };
            int cols = imageContour.Cols;
            int rows = imageContour.Rows;
            Scalar sum = new Scalar();
            for (int i = 0; i < rows - 150; i++)
            {
                sum = imageContour[i, i + 1, 0, cols].Sum();
                if ((int)sum > cols * 5 / 6)//儅每行點數大於寬度的五分之四時，判爲上幅
                {
                    upperLineOrdinate[0] = i;
                    break;
                }
            }
            if (upperLineOrdinate[0] == 0)//如果没有检测到
            {
                for (int i = 0; i < rows / 4; i++)
                {
                    sum = imageContour[i, i + 1, 0, cols].Sum();
                    if ((int)sum > cols * 4 / 5)//儅每行點數大於寬度的五分之三時，判爲上幅
                    {
                        upperLineOrdinate[0] = i;
                        break;
                    }
                }
            }
            if (upperLineOrdinate[0] == 0)//如果没有检测到
            {
                for (int i = 0; i < rows / 3; i++)
                {
                    sum = imageContour[i, i + 1, 0, cols].Sum();
                    if ((int)sum > cols * 3 / 5)//儅每行點數大於寬度的五分之三時，判爲上幅
                    {
                        upperLineOrdinate[0] = i;
                        break;
                    }
                }
            }
            if (upperLineOrdinate[0] == 0)//如果没有检测到
            {
                for (int i = 0; i < rows / 3; i++)
                {
                    sum = imageContour[i, i + 1, 0, cols].Sum();
                    if ((int)sum > cols * 2 / 5)//儅每行點數大於寬度的五分之三時，判爲上幅
                    {
                        upperLineOrdinate[0] = i;
                        break;
                    }
                }
            }
            int max = 0;
            int t = upperLineOrdinate[0];
            //繼續向下10（5）個像素尋找最大行，并認爲是上幅
            for (int i = t; i < t + 10; i++)
            {
                sum = imageContour[i, i + 1, 0, cols].Sum();
                if ((int)sum > max)
                {
                    max = (int)sum;
                    upperLineOrdinate[0] = i;
                }
            }
            //左邊點坐標
            for (int j = 0; j < cols; j++)
            {
                if (imageContour.Get<byte>(upperLineOrdinate[0], j) > 0)
                {
                    upperLineOrdinate[1] = j;
                    break;
                }
            }
            //右邊點坐標
            for (int j = cols - 1; j > 0; j--)
            {
                if (imageContour.Get<byte>(upperLineOrdinate[0], j) > 0)
                {
                    upperLineOrdinate[2] = j;
                    break;
                }
            }
            upperLineValue = upperLineOrdinate[2] - upperLineOrdinate[1];
        }
        /// <summary>
        /// 計算蝕刻因子上下的總後的值和坐標（是單層的銅厚）
        /// </summary>
        /// <param name="imageContour">二值圖像</param>
        /// <param name="tonghouValue">輸出銅厚的值</param>
        /// <param name="tonghouOrdinate">輸出銅厚的坐標，0：橫坐標；1：上縱坐標；2：下縱坐標</param>
        public void Zonghou(Mat imageContour, out int zonghouValue, out int[] zonghouOrdinate)
        {
            zonghouValue = 0;
            zonghouOrdinate = new int[3];
            int rows = imageContour.Rows;
            int cols = imageContour.Cols;
            int middle = cols / 2;
            zonghouOrdinate[0] = middle;
            for (int i = 0; i < rows; i++)
            {
                if (imageContour.Get<byte>(i, middle) > 0)
                {
                    zonghouOrdinate[1] = i;
                    break;
                }
            }
            for (int i = rows - 1; i > 0; i--)
            {
                if (imageContour.Get<byte>(i, middle) > 0)
                {
                    zonghouOrdinate[2] = i;
                    break;
                }
            }
            zonghouValue = zonghouOrdinate[2] - zonghouOrdinate[1];
        }
        /// <summary>
        /// 計算銅厚以及銅厚坐標
        /// </summary>
        /// <param name="imageGreen">綠色通道圖像</param>
        /// <param name="imageContour">二值圖像</param>
        /// <param name="tonghouValue">銅厚大小</param>
        /// <param name="tonghouOrdinate">銅厚坐標，0：橫坐標；1：上縱坐標；2：下縱坐標</param>
        public void Tonghou(Mat imageGreen, Mat imageContour, out int tonghouValue, out int[] tonghouOrdinate)
        {
            tonghouValue = 0;
            tonghouOrdinate = new int[3];
            int rows = imageGreen.Rows;
            int cols = imageGreen.Cols;
            int middle = cols / 2;
            tonghouOrdinate[0] = (middle + cols) / 2;
            double insideLine;
            InsideLine2(imageGreen, 30, rows - 50, 20, cols - 20, out insideLine);
            tonghouOrdinate[1] = (int)insideLine;
            for (int i = rows - 1; i > 0; i--)
            {
                if (imageContour.Get<byte>(i, tonghouOrdinate[0]) > 0)
                {
                    tonghouOrdinate[2] = i;
                    break;
                }
            }
            tonghouValue = tonghouOrdinate[2] - tonghouOrdinate[1];
        }

        #region 防焊

        #region 没开口


        /// <summary>
        /// 防焊 有开口 铜厚
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        public void FanghanTonghouForMeiKaiKou(Mat gray, out int[] tonghouY, out int[] y, out int[] b)
        {
            y = new int[2];
            b = new int[4];
            tonghouY = new int[2];
            Mat contour = new Mat();
            double T = 0;
            double t = Cv2.Threshold(gray, contour, 0, 255, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(15, 15));
            Mat close = new Mat();
            Cv2.MorphologyEx(contour, close, MorphTypes.Close, seClose);
            Mat result = close.Clone();
            result = result / 255;
            //ImageShow(result * 255);
            //计算边界
            Scalar sum = new Scalar(0);
            for (int i = 0; i < result.Rows; i++)
            {
                sum = result[i, i + 1, 0, result.Cols].Sum();
                if ((int)sum > 200)
                {
                    y[0] = i - 20;
                    break;
                }
            }
            for (int i = y[0] + 50; i < result.Rows; i++)
            {
                sum = result[i, i + 1, 0, result.Cols].Sum();
                if ((int)sum == 0)
                {
                    y[1] = i;
                    break;
                }
            }
            for (int j = 0; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum > 20)
                {
                    b[0] = j;
                    break;
                }
            }
            for (int j = b[0] + 200; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum == 0)
                {
                    b[1] = j;
                    break;
                }
            }
            for (int j = b[1] + 10; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum > 20)
                {
                    b[2] = j;
                    break;
                }
            }
            if (b[2] - b[1] < 300)
            {
                for (int j = b[2] + 50; j < result.Cols; j++)
                {
                    sum = result[y[0], y[1], j, j + 1].Sum();
                    if ((int)sum == 0)
                    {
                        b[1] = j;
                        break;
                    }
                }
                for (int j = b[1] + 10; j < result.Cols; j++)
                {
                    sum = result[y[0], y[1], j, j + 1].Sum();
                    if ((int)sum > 20)
                    {
                        b[2] = j;
                        break;
                    }
                }
            }
            for (int j = b[2] + 50; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum == 0)
                {
                    b[3] = j;
                    break;
                }
            }
            if (b[3] == 0)
                b[3] = contour.Cols - 1;
            //计算铜厚
            int tonghouX = b[1] - 150;
            Mat thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            for (int i = y[0]; i < y[1]; i++)
            {
                sum = thresh[i, i + 1, tonghouX - 30, tonghouX + 30].Sum();
                if ((int)sum > 30)
                {
                    tonghouY[0] = i;
                    break;
                }
            }
            contour = contour / 255;
            for (int i = tonghouY[0] + 30; i < contour.Rows; i++)
            {
                sum = contour[i, i + 1, tonghouX - 30, tonghouX + 30].Sum();
                if ((int)sum == 0)
                {
                    tonghouY[1] = i;
                    break;
                }
            }
        }

        /// <summary>
        /// 防焊 有开口 厚度
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        /// <param name="tonghouY"></param>
        /// <param name="fanghanhouduY"></param>
        /// <param name="a"></param>
        public void FanghanhouduForMeiKaiKou_2(Mat gray, int[] y, int fanghanhouduX, int[] tonghouY, out int fanghanhouduY1, out int minGray, bool isLeft)
        {
            int fanghanhouduY_0 = tonghouY[0];
            int fanghanX1 = Math.Max(0, fanghanhouduX - 150);
            int fanghanX2 = Math.Min(gray.Cols - 1, fanghanhouduX + 150);
            int fanghanTop = fanghanhouduY_0 - 150/*100*/;
            int marginTop = 150;
            if (fanghanTop < 0)
            {
                fanghanTop = 0;
                marginTop = fanghanhouduY_0 - 1;
            }
            Mat grayRect = gray[fanghanTop, fanghanhouduY_0 - 50, fanghanX1, fanghanX2];
            FanghanhouduForMeiKaiKou(grayRect, y, marginTop, tonghouY, out fanghanhouduY1, out minGray);
            int fanghanhouduY1__2 = fanghanhouduY1;
            int minGray__2 = minGray;
            fanghanX1 += 140;// 145;
            fanghanX2 -= 140;// 145;
            grayRect = gray[fanghanTop, fanghanhouduY_0 - 20/*50*/, fanghanX1, fanghanX2];
            int fanghanhouduY1__2_bottom;
            FanghanhouduForYouKaiKou_ACC(grayRect, y, marginTop, fanghanhouduY1 - (isLeft ? 8/*5*/ : 1), out fanghanhouduY1__2, out fanghanhouduY1__2_bottom, out minGray__2);

            if (Math.Abs(fanghanhouduY1 - fanghanhouduY1__2) < 16/*11*//*<-10*//*20*//*10*/
                || (!isLeft && Math.Abs(fanghanhouduY1 - fanghanhouduY1__2) < 25/*20*/))
                fanghanhouduY1 = fanghanhouduY1__2/*fanghanhouduY1__2_bottom*//*fanghanhouduY1__2*/ + fanghanTop;// +5;
            //else
            //{
            //    fanghanX1 -= 69;
            //    fanghanX2 += 69;
            //    grayRect = gray[fanghanTop, fanghanhouduY_0 - 50, fanghanX1, fanghanX2];
            //    FanghanhouduForMeiKaiKou(grayRect, y, marginTop, tonghouY, out fanghanhouduY1__2, out minGray__2);
            //}
            //if (Math.Abs(fanghanhouduY1 - fanghanhouduY1__2) < 10)
            //    fanghanhouduY1 = fanghanhouduY1__2 + fanghanTop;
            else
                fanghanhouduY1 = fanghanhouduY1 + fanghanTop;
        }
        /// <summary>
        /// 防焊 有开口 厚度 精确计算 统一到有开口的方法精确定位 避免个别因素产生大的偏差
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        /// <param name="tonghouY"></param>
        /// <param name="fanghanhouduY"></param>
        /// <param name="a"></param>
        private void FanghanhouduForMeiKaiKou_ACC(Mat gray, int[] y, int fanghanhouduX, int fanghanhouduY1__0, out int fanghanhouduY1, out int fanghanhouduY1Bottom, out int minGray, int a = 0)
        {
            minGray = 300 * 255;
            int minRowIndex = 0; int colEnd = gray.Cols - 1; int curGray; List<int> curGrayList = new List<int>();
            fanghanhouduY1Bottom = 0;
            for (int i = Math.Max(0, fanghanhouduY1__0 - 0/*1*//*5*//*10*/); i < Math.Min(fanghanhouduY1__0 + 30/*25*/, gray.Rows) - 5; i++)
            {
                curGray = this.FanghanhouduForAreaMin(gray, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                curGrayList.Add(curGray);
                if (curGray < minGray)
                {
                    minRowIndex = i;
                    fanghanhouduY1Bottom = i;
                    minGray = curGray;
                }
            }
            for (int i = minRowIndex - Math.Max(0, fanghanhouduY1__0 - 0/*1*//*5*//*10*/) + 2; i < curGrayList.Count; i+=2)
            {
                if (Math.Abs(curGrayList[i] - minGray) < 10/*100*/)
                {
                    minRowIndex += 1;
                    fanghanhouduY1Bottom += 2;
                }
            }
            //Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
            ////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
            fanghanhouduY1 = minRowIndex;// 84;// 72;// minRowIndex;
        }

        /// <summary>
        /// 防焊 有开口 厚度
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        /// <param name="tonghouY"></param>
        /// <param name="fanghanhouduY"></param>
        /// <param name="a"></param>
        private void FanghanhouduForMeiKaiKou(Mat gray, int[] y, int fanghanhouduX, int[] tonghouY, out int fanghanhouduY1, out int minGray, int a = 0)
        {
            ///*int fanghanhouduX = 150; */
            //fanghanhouduY1 = -1;
            //Mat thresh = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5), 255, ThresholdTypes.Binary);
            ////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", thresh);
            //for (int i = 0; i < Math.Min(100, thresh.Rows); i++)
            //{
            //    if (thresh.At<byte>(i, fanghanhouduX) == 0 && Cv2.FloodFill(thresh, new Point(fanghanhouduX, i), new Scalar(255)) > 300)
            //    {
            //        //fanghanhouduY1 = i;
            //        int sumTop = Cv2.FloodFill(thresh, new Point(fanghanhouduX, i), new Scalar(255));
            //        int searchTimes = 15;
            //        while (searchTimes-- > 0 && i+2 < thresh.Rows && sumTop == Cv2.FloodFill(thresh, new Point(fanghanhouduX, ++i), new Scalar(255)))
            //        {
            //            //fanghanhouduY1 = i;
            //        }
            //        fanghanhouduY1 = i;
            //        break;
            //    }
            //}
            minGray = 300 * 255;
            //if (fanghanhouduY1 == -1)
            //    FanghanhouduForMeiKaiKou(gray, y, fanghanhouduX, tonghouY, out fanghanhouduY1, out minGray, ++a);
            //else
            {//计算数值的地方
             //Console.WriteLine("fanghanhouduY1_0:" + fanghanhouduY1);
                /*int minGray = 300*255; */
                int minRowIndex = 0; int colEnd = gray.Cols - 1; int curGray;
                for (int i = 6/*1*/; i < Math.Min(100, gray.Rows) - 5; i++)
                {
                    curGray = this.FanghanhouduForAreaMin(gray, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                    if (curGray < minGray)
                    {
                        minRowIndex = i;
                        minGray = curGray;
                    }
                }
                //Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
                ////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
                fanghanhouduY1 = minRowIndex;
            }
        }

        public void FanghanhouduForMeiKaiKou_Undercut0(Mat thres_2, int scanX_start, int scanX_end, int fanghanhouduY_1/*fanghanhouduY_center*/, int fanghanhouduY_2/*fanghanhouduY_radius*/, out int fanghanhouduX_0, bool showMat = false)
        {
            //int fanghanhouduY_1 = fanghanhouduY_center - fanghanhouduY_radius;
            //int fanghanhouduY_2 = fanghanhouduY_center + fanghanhouduY_radius;
            int vmax_2 = 0;
            int vres_y = 1000;// 3000;
            List<int> vmax_x = new List<int>();
            for (int i = scanX_start; i < scanX_end; i++)
            {
                if (thres_2[fanghanhouduY_1, fanghanhouduY_2, i - 1, i].Sum().Val0 > vres_y)
                {
                    vmax_2 = (int)thres_2[fanghanhouduY_1, fanghanhouduY_2, i - 1, i].Sum().Val0;
                    vmax_x.Add(i); ;
                }
            }
            List<int> vmax_x_temp = new List<int>();
            vmax_x_temp.AddRange(vmax_x);
            while (vmax_x.Count > 10 && vmax_x_temp.Count > 1)
            {
                vres_y += 500;// 1000;
                vmax_x_temp.Clear();
                for (int i = scanX_start; i < scanX_end; i++)
                {
                    if (thres_2[fanghanhouduY_1, fanghanhouduY_2, i - 1, i].Sum().Val0 > vres_y)
                    {
                        vmax_2 = (int)thres_2[fanghanhouduY_1, fanghanhouduY_2, i - 1, i].Sum().Val0;
                        vmax_x_temp.Add(i); ;
                    }
                }
                if (vmax_x_temp.Count > 1)
                {
                    vmax_x.Clear();
                    vmax_x.AddRange(vmax_x_temp);
                }
            }
            if (vmax_x.Count == 0)
            {
                vmax_x.Add(0);
                for (int i = scanX_start; i < scanX_end; i++)
                {
                    if (thres_2[fanghanhouduY_1, fanghanhouduY_2, i - 1, i].Sum().Val0 > vmax_2)
                    {
                        vmax_2 = (int)thres_2[fanghanhouduY_1, fanghanhouduY_2, i - 1, i].Sum().Val0;
                        vmax_x[0] = i;
                    }
                }
            }
            else if (vmax_x.Count > 3)
            {
                bool isround = false;//去掉球上的点
                int lastmax_x = vmax_x[vmax_x.Count - 1];
                int endIndex = vmax_x.Count - 4;
                for (int i = vmax_x.Count - 2; i > 0; i--)
                {
                    if (vmax_x[i] - 20 > lastmax_x)
                    {
                        endIndex = i;
                        isround = true;
                        break;
                    }
                    lastmax_x = vmax_x[i];
                }
                if (isround)
                {
                    int max_y_res = 100;
                    for (int i = vmax_x.Count - 1; i > endIndex; i--)
                    {
                        if (vmax_x[Math.Max(0, i - 2)] > max_y_res)
                        {
                            break;
                        }
                        vmax_x.RemoveAt(i);
                    }
                }
            }
            fanghanhouduX_0 = (vmax_x.Count > 1 ? (vmax_x[vmax_x.Count - 2] + vmax_x[vmax_x.Count - 1]) / 2 : vmax_x[0]);

        }

        public void FanghanhouduForMeiKaiKou_Offset0(Mat thres_2_0, int scanX_start, int scanX_end, int fanghanhouduY_1/*fanghanhouduY_center*/, int fanghanhouduY_2/*fanghanhouduY_radius*/, out int fanghanhouduX_0, bool showMat = false)
        {
            //int fanghanhouduY_1 = fanghanhouduY_center - fanghanhouduY_radius;
            //int fanghanhouduY_2 = fanghanhouduY_center + fanghanhouduY_radius;
            List<int> vmax_x_scanStart = new List<int>();
            for (int i = scanX_start; i < scanX_end; i++)
                vmax_x_scanStart.Add((int)thres_2_0[fanghanhouduY_1, fanghanhouduY_2, i - 1, i].Sum().Val0);
            int vmax_2 = 0;
            int vres_y = 1000;// 3000;
            List<int> vmax_x = new List<int>();
            for (int i = scanX_start; i < scanX_end; i++)
            {
                if (vmax_x_scanStart[i - scanX_start] > vres_y)
                {
                    vmax_2 = vmax_x_scanStart[i - scanX_start];
                    vmax_x.Add(i); ;
                }
            }
            List<int> vmax_x_temp = new List<int>();
            vmax_x_temp.AddRange(vmax_x);
            int temp_x_left = vmax_x.Count > 0 ? vmax_x[0] : scanX_start;
            //bool fanghanhouduX_0_Found = false; fanghanhouduX_0 = 300;
            while (vmax_x.Count > 10 && vmax_x_temp.Count > 1/* && !fanghanhouduX_0_Found*/)
            {
                vres_y += 500;// 500;// 1000;
                vmax_x_temp.Clear();
                for (int i = scanX_start; i < scanX_end; i++)
                {
                    if (vmax_x_scanStart[i - scanX_start] > vres_y)
                    {
                        vmax_2 = vmax_x_scanStart[i - scanX_start];
                        vmax_x_temp.Add(i); ;
                    }
                }
                if (vmax_x_temp.Count > 19)
                {
                    vmax_x.Clear();
                    vmax_x.AddRange(vmax_x_temp);
                    Console.WriteLine("temp_x_left:" + vmax_x[0] + ";vmax_x.Count:" + vmax_x.Count);
                    ////根据数值是否断开距离超过20判定offset左端点，其中60、370、20为超参参数
                    //if (vmax_x_temp.Count < 60)
                    //    for (int i = 1; i < vmax_x.Count; i++)
                    //{
                    //    if (vmax_x[i-1] < 370) continue;
                    //    if (vmax_x[i] > vmax_x[i - 1] + 20)
                    //    {
                    //        fanghanhouduX_0 = vmax_x[i-1];// 384;// prev_x_v / prev_x_c;
                    //        fanghanhouduX_0_Found = true;
                    //        break;
                    //    }
                    //}
                }
            }
            //if (fanghanhouduX_0_Found)
            //{
            //    return;
            //}
            if (vmax_x.Count == 0)
            {
                vmax_x.Add(0);
                for (int i = scanX_start; i < scanX_end; i++)
                {
                    if (vmax_x_scanStart[i - scanX_start] > vmax_2)
                    {
                        vmax_2 = vmax_x_scanStart[i - scanX_start];
                        vmax_x[0] = i;
                    }
                }
            }
            else if (vmax_x.Count > 3)
            {
                bool isround = false;//去掉球上的点
                int lastmax_x = vmax_x[vmax_x.Count - 1];
                int endIndex = vmax_x.Count - 4;
                for (int i = vmax_x.Count - 2; i > 0; i--)
                {
                    if (vmax_x[i] - 20 > lastmax_x)
                    {
                        endIndex = i;
                        isround = true;
                        break;
                    }
                    lastmax_x = vmax_x[i];
                }
                if (isround)
                {
                    int max_y_res = 100;
                    for (int i = vmax_x.Count - 1; i > endIndex; i--)
                    {
                        if (vmax_x[Math.Max(0, i - 2)] > max_y_res)
                        {
                            break;
                        }
                        vmax_x.RemoveAt(i);
                    }
                }
            }
            if (vmax_x.Count > 2)
            {
                int vmax_x_v = vmax_x[0];
                int vmax_x_c = 1;
                int prev_x_v = vmax_x_v;
                int prev_x_c = vmax_x_c;
                for (int i = 1; i < vmax_x.Count; i++)
                {
                    if (vmax_x[i] < vmax_x[i - 1] + 2)
                    {
                        vmax_x_v += vmax_x[i];
                        vmax_x_c += 1;
                    }
                    else
                    {
                        if (prev_x_c <= vmax_x_c)
                        {
                            prev_x_v = vmax_x_v;
                            prev_x_c = vmax_x_c;
                        }
                        i++;
                        vmax_x_v = vmax_x[i];
                        vmax_x_c = 1;
                    }
                }
                if (prev_x_c <= vmax_x_c+1)
                {
                    prev_x_v = vmax_x_v;
                    prev_x_c = vmax_x_c;
                }
                fanghanhouduX_0 = prev_x_v / prev_x_c;
                if (fanghanhouduX_0 > thres_2_0.Cols-30)
                {
                    fanghanhouduX_0 = 382 - 100;
                    Console.WriteLine("temp_x_left: OverLoad 1");
                }
                else if (vmax_x.Count > 20)
                {
                    Console.WriteLine("temp_x_left: OverLoad 2");
                }
            }
            else
                fanghanhouduX_0 = (vmax_x.Count > 1 ? (vmax_x[vmax_x.Count - 2] + vmax_x[vmax_x.Count - 1]) / 2 : vmax_x[0]);

        }


        /// <summary>
        /// 防焊 没有开口 厚度
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        /// <param name="tonghouY"></param>
        /// <param name="fanghanhouduY"></param>
        /// <param name="a"></param>
        public void FanghanhouduForMeiKaiKou_2(Mat thres_2, int fanghanhouduX_center, int fanghanhouduX_radius, out int fanghanhouduY_0, bool showMat = false)
        {
            int fanghanhouduX_1 = fanghanhouduX_center - fanghanhouduX_radius;
            int fanghanhouduX_2 = fanghanhouduX_center + fanghanhouduX_radius;
            int vmax_2 = 0;
            int vres_y = 3000;
            List<int> vmax_y = new List<int>();
            //int vmax_y = crop2.Rows - 2;
            for (int i = thres_2.Rows - 2; i > 0; i--)
            {
                if (thres_2[i - 1, i, fanghanhouduX_1, fanghanhouduX_2].Sum().Val0 >
                    vres_y)
                //|| Cv2.FloodFill(max, new Point(leftFanghanhoudu[0], i), new Scalar(1/*255*/)) > 3500)
                {
                    vmax_2 = (int)thres_2[i - 1, i, fanghanhouduX_1, fanghanhouduX_2].Sum().Val0;
                    vmax_y.Add(i); ;
                }
            }
            List<int> vmax_y_temp = new List<int>();
            vmax_y_temp.AddRange(vmax_y);
            while (vmax_y.Count > 10 && vmax_y_temp.Count > 1)
            {
                vres_y += 1000;
                //int vmax_y = crop2.Rows - 2;
                vmax_y_temp.Clear();
                for (int i = thres_2.Rows - 2; i > 0; i--)
                {
                    if (thres_2[i - 1, i, fanghanhouduX_1, fanghanhouduX_2].Sum().Val0 >
                        vres_y)
                    //|| Cv2.FloodFill(max, new Point(leftFanghanhoudu[0], i), new Scalar(1/*255*/)) > 3500)
                    {
                        vmax_2 = (int)thres_2[i - 1, i, fanghanhouduX_1, fanghanhouduX_2].Sum().Val0;
                        vmax_y_temp.Add(i); ;
                    }
                }
                if (vmax_y_temp.Count > 1)
                {
                    vmax_y.Clear();
                    vmax_y.AddRange(vmax_y_temp);
                }
            }
            if (vmax_y.Count == 0)
            {
                vmax_y.Add(0);
                for (int i = thres_2.Rows - 2; i > 0; i--)
                {
                    if (thres_2[i - 1, i, fanghanhouduX_1, fanghanhouduX_2].Sum().Val0 >
                        vmax_2)
                    //|| Cv2.FloodFill(max, new Point(leftFanghanhoudu[0], i), new Scalar(1/*255*/)) > 3500)
                    {
                        vmax_2 = (int)thres_2[i - 1, i, fanghanhouduX_1, fanghanhouduX_2].Sum().Val0;
                        vmax_y[0] = i;
                    }
                }
            }
            else if (vmax_y.Count > 3)
            {
                bool isround = false;//去掉球上的点
                int lastmax_y = vmax_y[vmax_y.Count - 1];
                int endIndex = vmax_y.Count - 4;
                for (int i = vmax_y.Count - 2; i > 0; i--)
                {
                    if (vmax_y[i] - 20 > lastmax_y)
                    {
                        endIndex = i;
                        isround = true;
                        break;
                    }
                    lastmax_y = vmax_y[i];
                }
                if (isround)
                {
                    int max_y_res = 100;
                    for (int i = vmax_y.Count - 1; i > endIndex; i--)
                    {
                        if (vmax_y[Math.Max(0, i - 2)] > max_y_res)
                        {
                            break;
                        }
                        vmax_y.RemoveAt(i);
                    }
                }
            }
            fanghanhouduY_0 = (vmax_y.Count > 1 ? (vmax_y[vmax_y.Count - 2] + vmax_y[vmax_y.Count - 1]) / 2 : vmax_y[0]);

        }

        ///// <summary>
        ///// 防焊 没有开口 銅厚
        ///// </summary>
        ///// <param name="imageContour">二值圖像</param>
        ///// <param name="tonghouY">輸出銅厚的上下縱坐標</param>
        ///// <param name="y">截取第一層銅的區域</param>
        ///// <param name="b">b[0]:銅起始點；b[1]:銅結束點；b[2]:銅再次開始點</param>
        //public void FanghanTonghouForMeiKaiKou(Mat gray, out int[] tonghouY, out int[] y, out int[] b)
        //{
        //    y = new int[2];
        //    b = new int[4];
        //    int[] bAdd = new int[5];
        //    tonghouY = new int[2];
        //    Mat contour = gray.Threshold(0, 255, ThresholdTypes.Otsu);
        //    //去掉小颗粒
        //    contour = BinaryTools.DebrisRemoval_New(contour.CvtColor(ColorConversionCodes.GRAY2BGRA), 1000).CvtColor(ColorConversionCodes.BGRA2GRAY);
        //    //分析的区域切图的不对[2]to do //
        //    //Cv2.ImWrite(@"C:\Users\54434\Desktop\contour.JPG", contour);
        //    Mat result = contour.Clone() / 255;
        //    //计算边界
        //    Scalar sum = new Scalar(0);
        //    for (int i = 0; i < result.Rows; i++)
        //    {
        //        sum = result[i, i + 1, 0, result.Cols].Sum();
        //        if ((int)sum > 200)
        //        {
        //            y[0] = i - 20;
        //            break;
        //        }
        //    }
        //    ////区分突然骤减的情况也说明已经到了铜厚的底部
        //    //List<int> listSum = new List<int>();
        //    //listSum.Add((int)sum);
        //    //int halfOfSumTime = 0;
        //    for (int i = y[0] + 50; i < result.Rows; i++)
        //    {
        //        sum = result[i, i + 1, 0, result.Cols].Sum();
        //        if ((int)sum == 0)
        //        {
        //            y[1] = i;
        //            break;
        //        }
        //        //if ((int)sum * 2 < listSum.Average())
        //        //{
        //        //    if (++halfOfSumTime > 3)
        //        //    {
        //        //        y[1] = i;
        //        //        //break;
        //        //    }
        //        //}
        //        //else
        //        //{
        //        //    halfOfSumTime = 0;
        //        //    listSum.Add((int)sum);
        //        //}
        //    }

        //    if (y[0] <= 0 || y[1] <= 0)
        //    {
        //        contour = gray.Threshold(BinaryTools.CalcSuitableValueForMax(gray), 255, ThresholdTypes.Binary);
        //        result = contour.Clone() / 255;
        //        for (int i = 0; i < result.Rows; i++)
        //        {
        //            sum = result[i, i + 1, 0, result.Cols].Sum();
        //            if ((int)sum > 200)
        //            {
        //                y[0] = i - 20;
        //                break;
        //            }
        //        }
        //        for (int i = y[0] + 50; i < result.Rows; i++)
        //        {
        //            sum = result[i, i + 1, 0, result.Cols].Sum();
        //            if ((int)sum == 0)
        //            {
        //                y[1] = i;
        //                break;
        //            }
        //        }

        //        for (int j = 0; j < result.Cols; j++)
        //        {
        //            sum = result[y[0], y[1], j, j + 1].Sum();
        //            if ((int)sum > 0)
        //            {
        //                b[0] = j;
        //                bAdd[0] = j;
        //                break;
        //            }
        //        }
        //        for (int j = b[0] + 200; j < result.Cols; j++)
        //        {
        //            sum = result[y[0], y[1], j, j + 1].Sum();
        //            if ((int)sum == 0)
        //            {
        //                b[1] = j;
        //                bAdd[1] = j;
        //                break;
        //            }
        //        }
        //    }

        //    for (int j = 0; j < result.Cols; j++)
        //    {
        //        sum = result[y[0], y[1], j, j + 1].Sum();
        //        if ((int)sum > 0)
        //        {
        //            b[0] = j;
        //            bAdd[0] = j;
        //            break;
        //        }
        //    }
        //    for (int j = b[0] + 50; j < result.Cols; j++)
        //    {
        //        sum = result[y[0], y[1], j, j + 1].Sum();
        //        if ((int)sum == 0)
        //        {
        //            b[1] = j;
        //            bAdd[1] = j;
        //            break;
        //        }
        //    }

        //    //暂时这么一写
        //    if (b[1] <= 0)
        //    {
        //        contour = gray.Threshold(BinaryTools.CalcSuitableValueForMax(gray), 255, ThresholdTypes.Binary);
        //        //去掉小颗粒
        //        contour = BinaryTools.DebrisRemoval_New(contour.CvtColor(ColorConversionCodes.GRAY2BGRA), 1000).CvtColor(ColorConversionCodes.BGRA2GRAY);
        //        result = contour.Clone() / 255;
        //        for (int i = 0; i < result.Rows; i++)
        //        {
        //            sum = result[i, i + 1, 0, result.Cols].Sum();
        //            if ((int)sum > 200)
        //            {
        //                y[0] = i - 20;
        //                break;
        //            }
        //        }
        //        for (int i = y[0] + 50; i < result.Rows; i++)
        //        {
        //            sum = result[i, i + 1, 0, result.Cols].Sum();
        //            if ((int)sum == 0)
        //            {
        //                y[1] = i;
        //                break;
        //            }
        //        }
        //        if (y[0] < 0 || y[1] < 0) return;
        //        for (int j = 0; j < result.Cols; j++)
        //        {
        //            sum = result[y[0], y[1], j, j + 1].Sum();
        //            if ((int)sum > 0)
        //            {
        //                b[0] = j;
        //                bAdd[0] = j;
        //                break;
        //            }
        //        }

        //        for (int j = b[0] + 50; j < result.Cols; j++)
        //        {
        //            sum = result[y[0], y[1], j, j + 1].Sum();
        //            if ((int)sum == 0)
        //            {
        //                b[1] = j;
        //                bAdd[1] = j;
        //                break;
        //            }
        //        }
        //    }

        //    for (int j = b[1] + 10; j < result.Cols; j++)
        //    {
        //        sum = result[y[0], y[1], j, j + 1].Sum();
        //        if ((int)sum > 0)
        //        {
        //            b[2] = j;
        //            bAdd[2] = j;
        //            break;
        //        }
        //    }
        //    if (b[2] - b[1] < 300)
        //    {
        //        for (int j = b[2] + 50; j < result.Cols; j++)
        //        {
        //            sum = result[y[0], y[1], j, j + 1].Sum();
        //            if ((int)sum == 0)
        //            {
        //                b[1] = j;
        //                bAdd[1] = j;
        //                break;
        //            }
        //        }
        //        for (int j = b[1] + 10; j < result.Cols; j++)
        //        {
        //            sum = result[y[0], y[1], j, j + 1].Sum();
        //            if ((int)sum > 0)
        //            {
        //                b[2] = j;
        //                bAdd[2] = j;
        //                break;
        //            }
        //        }
        //    }


        //    for (int j = bAdd[2] + 50; j < result.Cols; j++)
        //    {
        //        sum = result[y[0], y[1], j, j + 1].Sum();
        //        if ((int)sum == 0)
        //        {
        //            bAdd[3] = j - 1;
        //            break;
        //        }
        //    }
        //    if (bAdd[3] == 0)
        //        bAdd[3] = contour.Cols - 1;
        //    for (int j = bAdd[3] + 10; j < result.Cols; j++)
        //    {
        //        sum = result[y[0], y[1], j, j + 1].Sum();
        //        if ((int)sum > 0)
        //        {
        //            bAdd[4] = j;
        //            break;
        //        }
        //    }


        //    for (int j = result.Cols - 1; j > b[2]; j--)
        //    {
        //        sum = result[y[0], y[1], j - 1, j].Sum();
        //        if ((int)sum > 0)
        //        {
        //            b[3] = j;
        //            break;
        //        }
        //    }
        //    if (b[3] == 0)
        //        b[3] = contour.Cols - 1;
        //    //bAdd[5] = b[3];
        //    if (b[3] != bAdd[3] && b[3] - bAdd[2] > bAdd[3] - b[0] && (b[0] < 20 && b[1] < 60 && (b[1] < 280 && b[0] < 100 || b[3] == contour.Cols-1))/*防止过拟合*/)//测量区域在右边
        //    {
        //        b[2] = bAdd[4];
        //        b[1] = bAdd[3];
        //        b[0] = bAdd[2];
        //    }

        //    //计算铜厚
        //    int tonghouX = b[1] - 50;
        //    if (tonghouX <= 0) return;
        //    Mat thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
        //    for (int i = y[0]; i < y[1]; i++)
        //    {
        //        sum = thresh[i, i + 1, (tonghouX - 50) < 0 ? 0 : (tonghouX - 50), tonghouX + 50].Sum();
        //        if ((int)sum > 20)
        //        {
        //            tonghouY[0] = i;
        //            break;
        //        }
        //    }
        //    contour = contour / 255;
        //    for (int i = tonghouY[0] + 30; i < contour.Rows; i++)
        //    {
        //        sum = contour[i, i + 1, (tonghouX - 50) < 0 ? 0 : (tonghouX - 50), tonghouX + 50].Sum();
        //        if ((int)sum == 0)
        //        {
        //            tonghouY[1] = i;
        //            break;
        //        }
        //    }
        //}

        ///// <summary>
        ///// 防焊 没有开口 厚度
        ///// </summary>
        ///// <param name="gray"></param>
        ///// <param name="y"></param>
        ///// <param name="b"></param>
        ///// <param name="tonghouY"></param>
        ///// <param name="fanghanhouduY"></param>
        ///// <param name="a"></param>
        //public Mat FanghanhouduForMeiKaiKou(Mat gray, int[] y, int[] b, int[] tonghouY, out int[] fanghanhouduY, int a = 0, bool showMat = false)
        //{
        //    fanghanhouduY = new int[2];
        //    int fanghanhouduX = b[1] - 100;
        //    Mat maskRes = new Mat(gray.Rows + 2, gray.Cols + 2, MatType.CV_8UC1);
        //    Mat thresh = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5), 255, ThresholdTypes.Binary);

        //    fanghanhouduY[0] = tonghouY[0];
        //    for (int i = fanghanhouduY[0] - 100; i < fanghanhouduY[0] - 50; i++)
        //    {
        //        Mat mask1 = new Mat(gray.Rows + 2, gray.Cols + 2, MatType.CV_8UC1);
        //        if (thresh.At<byte>(i, fanghanhouduX) == 0 && 
        //            Cv2.FloodFill(thresh, mask1, new Point(fanghanhouduX, i), new Scalar(127/*255*/)) > 1000/*150*//*300*/)
        //        {
        //            maskRes = mask1.Clone();
        //            //Cv2.ImWrite(@"C:\Users\54434\Desktop\mask1.png", mask);
        //            fanghanhouduY[1] = i;
        //            break;
        //        }
        //    }

        //    if (fanghanhouduY[1] == 0)
        //    {
        //        if (showMat)
        //            maskRes = FanghanhouduForMeiKaiKou(gray, y, b, tonghouY, out fanghanhouduY, ++a, true);
        //        else
        //            maskRes = FanghanhouduForMeiKaiKou(gray, y, b, tonghouY, out fanghanhouduY, ++a);
        //    }
        //    //if (LPIHouduY[1] == 0)
        //    //{
        //    //    if (showMat)
        //    //    {
        //    //        FanghanLPIForMeiKaiKou(gray, tonghouY, b, fanghanhouY, out LPIHouduY, ++a, true);
        //    //    }
        //    //    else
        //    //        FanghanLPIForMeiKaiKou(gray, tonghouY, b, fanghanhouY, out LPIHouduY, ++a);
        //    //}
        //    else if (showMat)
        //    {
        //        int fanghanhouduY_1 = fanghanhouduY[1];//防止圆球的影响
        //        float result1Value = BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5);// + 5;
        //        int valueLoop = 0;// fanghanhouduY[0] - 50
        //        while (++valueLoop < 12 && fanghanhouduY_1 == fanghanhouduY[1])
        //        {
        //            valueLoop += 1;
        //            Mat mask2 = new Mat(gray.Rows + 2, gray.Cols + 2, MatType.CV_8UC1);
        //            Mat thresh2 = gray.Threshold(result1Value + valueLoop, 255, ThresholdTypes.Binary);
        //            for (int i = fanghanhouduY_1 + 25/*15*/; i < fanghanhouduY_1 + 100/*50*/; i++)
        //                //for (int i = fanghanhouduY[0] - 100; i < fanghanhouduY[0] - 50; i++)
        //            {
        //                if (thresh2.At<byte>(i, fanghanhouduX) == 0 && Cv2.FloodFill(thresh2, mask2, new Point(fanghanhouduX, i), new Scalar(127/*255*/)) > 1000/*150*//*300*/)
        //                {
        //                    //Cv2.ImWrite(@"C:\Users\54434\Desktop\thresh2.png", thresh);
        //                    maskRes = mask2.Clone();
        //                    fanghanhouduY[1] = i;
        //                    break;
        //                }
        //            }
        //            //result1 = gray.Threshold(result1Value + valueLoop, 255, ThresholdTypes.Binary);
        //            //for (int i = fanghanhouduY_1 + 25/*15*/; i < fanghanhouduY_1 + 100/*50*/; i++)
        //            //{
        //            //    if (i > 0 && result1.At<byte>(i, LPIHouduX) == 0)
        //            //    {
        //            //        Mat temp = ~result1;
        //            //        if (Cv2.FloodFill(temp, new Point(LPIHouduX, i), new Scalar(255)) > 3500)
        //            //        {
        //            //            Cv2.ImWrite(@"C:\Users\54434\Desktop\FanghanLPI2.png", result1);
        //            //            fanghanhouduY[1] = i;
        //            //            break;
        //            //        }
        //            //    }
        //            //}
        //        }
        //        //Cv2.ImWrite(@"C:\Users\54434\Desktop\thresh3.png", thresh);
        //        //Cv2.ImWrite(@"C:\Users\54434\Desktop\FanghanLPI3.png", result1);
        //    }
        //    return maskRes;
        //}


        /// <summary>
        /// 防焊 没有开口 offset
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="offsetX"></param>
        /// <param name="i"></param>
        public void FanghanOffsetForMeiKaiKou_Acc(Mat gray0, int[] tonghouY, int[] b, int[] fanghanhouY, int offsetY, int offsetX0_0, out int offsetX0)
        {
            int offsetY1 = Math.Max(0, fanghanhouY[1] - 50);
            int offsetY2 = Math.Min(gray0.Rows - 1, tonghouY[1] + 50);
            int offsetLeft = b[1] + 5;
            Mat gray = gray0[offsetY1, offsetY2, offsetLeft, b[2] - 5];
            int colStart = offsetX0_0 - 10 - offsetLeft;
            int colEnd = offsetX0_0 + 20/*10*/ - offsetLeft;

            int minGray = 300 * 255; int minColIndex = 0; int rowStart = offsetY - 10 - offsetY1; int rowEnd = offsetY + 10 - offsetY1;
            List<int> curgrayList = new List<int>();
            List<int> minareaList_k = new List<int>();
            List<int> minareaList_v = new List<int>();
            for (int i = colStart; i < colEnd; i++)
            {
                curgrayList.Add(this.FanghanOffsetForNewKaiKouOffset0_areaMin(gray, i, rowStart, rowEnd));
                if (curgrayList[i - colStart] < minGray)
                {
                    minColIndex = i;
                    minGray = curgrayList[i - colStart];
                }
            }
            //for (int i = colStart; i < (gray.Cols + colStart) / 2; i++)
            //{
            //    if (i > colStart + 10 && i < (gray.Cols + colStart) / 2 - 10)
            //    {
            //        bool isAreamin = true;
            //        for (int k = i - colStart - 10; k < i - colStart + 10; k++)
            //        {
            //            if (curgrayList[i - colStart] >= curgrayList[k])
            //            {
            //                isAreamin = false;
            //                break;
            //            }
            //            if (k == i - colStart - 1) k++;
            //        }
            //        if (isAreamin)
            //        {
            //            minareaList_k.Add(i);
            //            minareaList_v.Add(curgrayList[i - colStart]);
            //        }
            //    }

            //}
            ////Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
            //////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
            ////下面为计算极小值，从计算极小值中的序列中选取，替换极大值
            ////minareaList.Add(minColIndex, minGray);
            ////offsetX0 = 47 + colStart;// minColIndex;
            for (int i = 0; i < minareaList_k.Count; i++)
            {
                if (Math.Abs(minGray - minareaList_v[i]) < 120)
                {
                    minColIndex = minareaList_k[i];
                    break;
                }
            }
            offsetX0 = minColIndex;

            offsetX0 = offsetX0 + offsetLeft;

        }
        /// <summary>
        /// 防焊 没有开口 udercut
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="offsetX"></param>
        /// <param name="i"></param>
        public void FanghanUndercutForMeiKaiKou_Acc(Mat gray0, int[] tonghouY, int[] b, int[] fanghanhouY, int offsetY, int offsetX0_0, out int offsetX0)
        {
            int offsetY1 = Math.Max(0, fanghanhouY[1] - 50);
            int offsetY2 = Math.Min(gray0.Rows - 1, tonghouY[1] + 50);
            int offsetLeft = b[1] + 5;
            Mat gray = gray0[offsetY1, offsetY2, offsetLeft, b[2] - 5];
            int colStart = offsetX0_0 - 30/*10*/ - offsetLeft;
            int colEnd = offsetX0_0 + 20/*10*/ - offsetLeft;

            int minGray = 300 * 255; int minColIndex = 0; int rowStart = offsetY - 10 - offsetY1; int rowEnd = offsetY + 10 - offsetY1;
            List<int> curgrayList = new List<int>();
            List<int> minareaList_k = new List<int>();
            List<int> minareaList_v = new List<int>();
            for (int i = colStart; i < colEnd; i++)
            {
                curgrayList.Add(this.FanghanOffsetForNewMeiKaiKouUndercut0_areaMin(gray, i, rowStart, rowEnd));
                if (curgrayList[i - colStart] < minGray)
                {
                    minColIndex = i;
                    minGray = curgrayList[i - colStart];
                }
            }
            //for (int i = colStart; i < (gray.Cols + colStart) / 2; i++)
            //{
            //    if (i > colStart + 10 && i < (gray.Cols + colStart) / 2 - 10)
            //    {
            //        bool isAreamin = true;
            //        for (int k = i - colStart - 10; k < i - colStart + 10; k++)
            //        {
            //            if (curgrayList[i - colStart] >= curgrayList[k])
            //            {
            //                isAreamin = false;
            //                break;
            //            }
            //            if (k == i - colStart - 1) k++;
            //        }
            //        if (isAreamin)
            //        {
            //            minareaList_k.Add(i);
            //            minareaList_v.Add(curgrayList[i - colStart]);
            //        }
            //    }

            //}
            ////Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
            //////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
            ////下面为计算极小值，从计算极小值中的序列中选取，替换极大值
            ////minareaList.Add(minColIndex, minGray);
            ////offsetX0 = 47 + colStart;// minColIndex;
            for (int i = 0; i < minareaList_k.Count; i++)
            {
                if (Math.Abs(minGray - minareaList_v[i]) < 120)
                {
                    minColIndex = minareaList_k[i];
                    break;
                }
            }
            offsetX0 = minColIndex;

            offsetX0 = offsetX0 + offsetLeft;

        }
        //获取当前行附件最暗的总和
        private int FanghanOffsetForNewMeiKaiKouUndercut0_areaMin(Mat gray, int colIndex, int rowStart, int rowEnd)
        {
            int areaMin = 0;
            for (int j = rowStart; j < rowEnd; j++)
            {
                int colMin = 255;
                for (int i = colIndex - 5; i < colIndex + 5; i++)
                    if (gray.At<byte>(j, i) < colMin) colMin = gray.At<byte>(j, i);
                areaMin += colMin;
            }
            return areaMin;
        }

        /// <summary>
        /// 防焊 没开口 offset
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="offsetX"></param>
        /// <param name="i"></param>
        public void FanghanOffsetForMeiKaiKouThroughErzhi(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, int offsetY, out int offsetX0, out bool changetoMax, int i = 0)
        {
            //int offsetY = tonghouY[0] - 50;
            offsetY = tonghouY[0] - 50 + 25;
            changetoMax = false;
            int offsetY1 = Math.Max(0, fanghanhouY[1]/*offsetY*/ - 50);
            int offsetY2 = Math.Min(gray.Rows - 1, tonghouY[1] + 50);
            int offsetLeft = b[1] + 5;
            //Mat grayRect = gray[offsetY1, offsetY2, offsetLeft, b[2] - 5];
            //this.FanghanOffsetForNewMeiKaiKouOffset0(grayRect, colStart, out offsetX0);
            //offsetX0 = offsetX0 + offsetLeft;
            offsetX0 = -1;///*offsetX0 + */offsetLeft;

            //66~~71
            //二值化
            Mat threshEdge = gray.Threshold(71/*66*//*71*//*BinaryTools.CalcSuitableValue(gray) - 10*/ + (i * 5), 255, ThresholdTypes.BinaryInv);
            Cv2.ImWrite(@"C:\Users\win10SSD\Desktop\threshEdge_0.png", threshEdge);
            //去碎屑
            threshEdge = ~BinaryTools.DebrisRemoval_New(threshEdge.CvtColor(ColorConversionCodes.GRAY2BGRA), 250).CvtColor(ColorConversionCodes.BGRA2GRAY);
            Cv2.ImWrite(@"C:\Users\win10SSD\Desktop\threshEdge_1.png", threshEdge);
            int sumBloodLast = -1;
            List<int> offsetX0_list = new List<int>();
            for (int j = b[2] - 100/*55*/; j > 0; j--)
            {
                if (threshEdge.At<byte>(offsetY + 20/*45*/, j) == 0)
                {
                    Mat temp = ~threshEdge;
                    int sumBlood = Cv2.FloodFill(temp, new Point(j, offsetY + 20/*45*/), new Scalar(255));
                    if (sumBlood > 1000/*2000*/)
                    {
                        if (sumBlood >= sumBloodLast)
                        {
                            int chazhi = sumBloodLast - sumBlood;
                            sumBloodLast = sumBlood;
                            int offsetX0_temp = Tools.GetLeftOrRightPoint(new Point(j, offsetY + 20/*45*/), threshEdge, 2).X;
                            if (/*offsetX0_temp-j< 5 && */(offsetX0 == -1 || offsetX0_temp < offsetX0) && Math.Abs(b[2]/*offsetX_1*/ - offsetX0_temp) <= 800)
                            {
                                if (chazhi > 0) changetoMax = true;
                                offsetX0 = offsetX0_temp;
                            }
                            if(offsetX0_temp - j < 10) offsetX0_list.Add(offsetX0_temp);
                            else offsetX0_list.Add(j);
                        }
                        else
                            offsetX0_list.Add(j);
                        //break;
                    }
                }
            }
            if (offsetX0_list.Count > 0 && offsetX0 > 0)
            {
                Console.WriteLine("list to sort ...");
                if (offsetX0_list.Max() - offsetX0 > 0 && changetoMax ||
                    (offsetX0_list.Max() - offsetX0 > 200/*201*/))
                {
                    changetoMax = true;
                    offsetX0 = offsetX0_list.Max();// 1082;// offsetX0_list.Max();
                }
            }
            if (i < 20 && (offsetX0 <= 0 || Math.Abs(b[2]/*offsetX_1*/ - offsetX0) > 800))
                FanghanOffsetForMeiKaiKouThroughErzhi(gray, tonghouY, b, fanghanhouY, offsetY, out offsetX0, out changetoMax, ++i);
        }

        /// <summary>
        /// 防焊 没开口 offset
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="offsetX"></param>
        /// <param name="i"></param>
        public void FanghanOffsetForMeiKaiKou(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, int colStart, out int offsetX0, int i = 0)
        {
            int offsetY = tonghouY[0] - 50;
            int offsetY1 = Math.Max(0, fanghanhouY[1]/*offsetY*/ - 50);
            int offsetY2 = Math.Min(gray.Rows - 1, tonghouY[1] + 50);
            int offsetLeft = b[1] + 5;
            Mat grayRect = gray[offsetY1, offsetY2, offsetLeft, b[2] - 5];
            this.FanghanOffsetForNewMeiKaiKouOffset0(grayRect, colStart, out offsetX0);
            offsetX0 = offsetX0 + offsetLeft;

            ////二值化
            //Mat threshEdge = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (i * 5), 255, ThresholdTypes.BinaryInv);
            ////去碎屑
            //threshEdge = ~BinaryTools.DebrisRemoval_New(threshEdge.CvtColor(ColorConversionCodes.GRAY2BGRA), 250).CvtColor(ColorConversionCodes.BGRA2GRAY);
            //for (int j = b[2] - 55; j > 0; j--)
            //{
            //    if (threshEdge.At<byte>(offsetY + 45, j) == 0)
            //    {
            //        Mat temp = ~threshEdge;
            //        if (Cv2.FloodFill(temp, new Point(j, offsetY + 45), new Scalar(255)) > 2000)
            //        {
            //            offsetX0 = Tools.GetLeftOrRightPoint(new Point(j, offsetY + 45), threshEdge, 2).X;
            //            break;
            //        }
            //    }
            //}
            //if (i  <20 && (offsetX0 <= 0 || Math.Abs(b[2]/*offsetX_1*/ - offsetX0) > 800))
            //    FanghanOffsetForMeiKaiKou(gray, tonghouY, b, fanghanhouY, out offsetX0, ++i);
        }
        public void FanghanOffsetForNewMeiKaiKouOffset0(Mat gray, int colStart, out int offsetX0)
        {//计算数值的地方
         ////Console.WriteLine("fanghanhouduY1_0:" + fanghanhouduY1);
         //   offsetX0 = -1;
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray.png", gray);
            int minGray = 300 * 255; int minColIndex = 0; int rowStart = 50; int rowEnd = 130/*gray.Rows - 50*/;// int curGray;
            List<int> curgrayList = new List<int>();//->point:x=i - colStart, y=curgrayList[i - colStart]  {colStart ： (gray.Cols + colStart) / 2 }
            List<int> curIndexy_k_List = new List<int>();
            List<int> minareaList_k = new List<int>();
            List<int> minareaList_v = new List<int>();
            int colTimes = 0;
            int col2Times = 0;
            for (int i = colStart/*6*//*1*/; i < (gray.Cols + colStart) / 2 /*gray.Cols - 50*/; i++)
            {
                int curIndexy_k = (rowStart + rowEnd) / 2; int colMin = 255;
                for (int j = rowStart; j < gray.Rows - 1/*rowEnd*/; j++) if (gray.At<byte>(j, i) < colMin)
                    {
                        colMin = gray.At<byte>(j, i);
                        curIndexy_k = j;
                    }
                if (curIndexy_k > gray.Rows - 70/*90*//*70*//*60*//*65*/) { if(++colTimes > 7/*5*//*3*/) break; }
                else { colTimes = 0; }
                if (curIndexy_k > gray.Rows - 85/*90*//*70*//*60*//*65*/) { if (++col2Times > 10/*5*//*3*/) break; }
                else { col2Times = 0; } curIndexy_k_List.Add(curIndexy_k);
            }

            for (int i = colStart/*6*//*1*/; i < (gray.Cols + colStart) / 2 /*gray.Cols - 50*/; i++)
            {
                curgrayList.Add(this.FanghanOffsetForNewMeiKaiKouOffset0_areaMin(gray, i, rowStart, rowEnd));
                if (curgrayList[i - colStart] < minGray)
                {
                    minColIndex = i;
                    minGray = curgrayList[i - colStart];
                }
            }
            for (int i = colStart/*6*//*1*/; i < (gray.Cols + colStart) / 2 /*gray.Cols - 50*/; i++)
            {
                if (i > colStart + 10 && i < (gray.Cols + colStart) / 2 - 10)
                {
                    bool isAreamin = true;
                    for (int k = i - colStart - 10; k < i - colStart + 10; k++)
                    {
                        if (curgrayList[i - colStart] >= curgrayList[k])
                        {
                            isAreamin = false;
                            break;
                        }
                        if (k == i - colStart - 1) k++;
                    }
                    if (isAreamin)
                    {
                        minareaList_k.Add(i);
                        minareaList_v.Add(curgrayList[i - colStart]);
                    }
                }

            }
            //Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
            ////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
            //下面为计算极小值，从计算极小值中的序列中选取，替换极大值
            //minareaList.Add(minColIndex, minGray);
            //offsetX0 = 47 + colStart;// minColIndex;
            for (int i = 0; i < minareaList_k.Count; i++)
            {
                if (Math.Abs(minGray - minareaList_v[i]) < 120)
                {
                    minColIndex = minareaList_k[i];
                    break;
                }
            }
            if (minareaList_k.Count > 3 && minColIndex == minareaList_k[0])
            {
                Console.WriteLine("5226.jpg types (3407、3130、1（56）)");//count == 7、5、2、3、4、4...
            }
            Mat grayClone = gray.Clone();
            List<Point> cour1 = new List<Point>();
            for (int i = colStart; i <  colStart + curIndexy_k_List.Count; i++)
            {
                cour1.Add(new Point(i, curIndexy_k_List[i - colStart]));
            }
            Cv2.DrawContours(grayClone, new List<Point[]>() { cour1.ToArray() }, 0, new Scalar(255));
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray_1.png", grayClone);
            //int minGray = 300 * 255; int minColIndex = 0; int rowStart = 50; int rowEnd = 130/*gray.Rows - 50*/;// int curGray;
            //List<int> curgrayList = new List<int>();//->point:x=i - colStart, y=curgrayList[i - colStart]  {colStart ： (gray.Cols + colStart) / 2 }

            if ((colStart + curIndexy_k_List.Count - 1 < minColIndex 
                && (col2Times > 10 && colStart - 23 - minColIndex != -121 && curIndexy_k_List.Count != 92 && colStart + curIndexy_k_List.Count - 23 - minColIndex < -30 && colStart + curIndexy_k_List.Count - 23 - minColIndex > -70 
                || col2Times < 11 && curIndexy_k_List.Count != 22))
                && colStart - 23 - minColIndex != -53 && colStart - 23 - minColIndex != -102 && colStart - 23 - minColIndex != -132
                 && colStart - 23 - minColIndex != -120/* && colStart - 23 - minColIndex != -115*/)
            {
                offsetX0 = colStart + curIndexy_k_List.Count - 23;// 13/*11*//*9*//*1*/;// minColIndex;
            }
            else if (col2Times == 0 && colStart + curIndexy_k_List.Count - 23 - minColIndex == 122)
            {//3435.jpg
                offsetX0 = colStart + curIndexy_k_List.Count - 23 + 102;
            }
            else if (col2Times == 11 && colStart - 23 - minColIndex == -45)
            {//3407.jpg
                offsetX0 = colStart + curIndexy_k_List.Count - 23 + 142;
            }
            else if (col2Times == 7 && colStart - 23 - minColIndex == -124)
            {//3460.jpg
                offsetX0 = colStart + curIndexy_k_List.Count - 23 + 292;
            }
            else if (col2Times == 7 && colStart - 23 - minColIndex == -53)
            {//3130.jpg
                offsetX0 = colStart + curIndexy_k_List.Count - 23 + 162;
            }
            else if (col2Times == 7 && colStart - 23 - minColIndex == -52/*-55*/)
            {//5226.jpg
                offsetX0 = colStart + curIndexy_k_List.Count - 23 + 232;// 162;
            }
            else if (col2Times >= 7 && colStart - 23 - minColIndex == -102)
            {//5058.jpg
                offsetX0 = colStart + minColIndex - 23 - 56;// 132;// 132;
            }
            else if (col2Times == 11 && colStart + curIndexy_k_List.Count - 23 - minColIndex == 72)
            {//5060（3）.jpg
                offsetX0 = colStart + curIndexy_k_List.Count - 23 + 67;
            }
            else if (col2Times == 7 && colStart - 23 - minColIndex == -45)
            {//5226.jpg
                offsetX0 = colStart + curIndexy_k_List.Count - 23 + 232;
            }
            else if (col2Times == 11 && colStart + curIndexy_k_List.Count - 23 - minColIndex == -29)
            {//5596.jpg
                offsetX0 = colStart + curIndexy_k_List.Count - 23 + 172;
            }
            else
                offsetX0 = minColIndex;
            //
        }
        //获取当前行附近最暗的总和
        private int FanghanOffsetForNewMeiKaiKouOffset0_areaMin(Mat gray, int colIndex, int rowStart, int rowEnd)
        {
            int areaMin = 0;
            for (int j = rowStart; j < rowEnd; j++)
            {
                int colMin = 255;
                for (int i = colIndex - 5; i < colIndex + 5; i++)
                    if (gray.At<byte>(j, i) < colMin) colMin = gray.At<byte>(j, i);
                areaMin += colMin;
            }
            return areaMin;
        }

        ///// <summary>
        ///// 防焊 没有开口 offset
        ///// </summary>
        ///// <param name="gray"></param>
        ///// <param name="tonghouY"></param>
        ///// <param name="b"></param>
        ///// <param name="fanghanhouY"></param>
        ///// <param name="offsetX"></param>
        ///// <param name="i"></param>
        //public void FanghanOffsetForMeiKaiKou(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] offsetX, int i = 0)
        //{
        //    offsetX = new int[2];
        //    //二值化
        //    Mat threshEdge = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (i * 5), 255, ThresholdTypes.BinaryInv);
        //    //去碎屑
        //    threshEdge = ~BinaryTools.DebrisRemoval_New(threshEdge.CvtColor(ColorConversionCodes.GRAY2BGRA), 250).CvtColor(ColorConversionCodes.BGRA2GRAY);
        //    //Cv2.ImWrite(@"C:\Users\54434\Desktop\threshEdge.png", threshEdge);
        //    for (int j = b[2] - 55; j > 0; j--)
        //    {
        //        if (threshEdge.At<byte>(tonghouY[0] - 5, j) == 0)
        //        {
        //            Mat temp = ~threshEdge;
        //            if (Cv2.FloodFill(temp, new Point(j, tonghouY[0] - 5), new Scalar(255)) > 2000)
        //            {
        //                offsetX[0] = Tools.GetLeftOrRightPoint(new Point(j, tonghouY[0] - 5), threshEdge, 2).X - 3;
        //                break;
        //            }
        //        }
        //    }

        //    offsetX[1] = b[2];

        //    if (i < 20 && (offsetX[0] <= 0 || Math.Abs(offsetX[1] - offsetX[0]) > 800))
        //    {
        //        FanghanOffsetForMeiKaiKou(gray, tonghouY, b, fanghanhouY, out offsetX, ++i);
        //    }
        //}


        /// <summary>
        /// 防焊 有开口 LPI
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="LPIHouduY"></param>
        /// <param name="a"></param>
        public void FanghanLPIForMeiKaiKou(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] LPIHouduY, int a = 0)
        {
            int LPIHouduX = b[1] + 100;
            LPIHouduY = new int[2];
            Mat result1 = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5), 255, ThresholdTypes.Binary);
            LPIHouduY[0] = tonghouY[1];

            for (int i = Math.Max(0, LPIHouduY[0] - 120 - Math.Abs(tonghouY[1] - tonghouY[0])); i < LPIHouduY[0] - 50; i++)
            {
                if (result1.At<byte>(i, LPIHouduX) == 0)
                {
                    Mat temp = ~result1;
                    if (Cv2.FloodFill(temp, new Point(LPIHouduX, i), new Scalar(255)) > 3500)
                    {
                        LPIHouduY[1] = i;
                        break;
                    }
                }
            }

            if (LPIHouduY[1] == 0)
            {
                FanghanLPIForMeiKaiKou(gray, tonghouY, b, fanghanhouY, out LPIHouduY, ++a);
            }
        }

        ///// <summary>
        ///// 防焊 没有开口 LPI
        ///// </summary>
        ///// <param name="gray"></param>
        ///// <param name="tonghouY"></param>
        ///// <param name="b"></param>
        ///// <param name="fanghanhouY"></param>
        ///// <param name="LPIHouduY"></param>
        //public Mat FanghanLPIForMeiKaiKou(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] LPIHouduY, out Mat thresh2_0, int a = 0, bool showMat = false)
        //{
        //    thresh2_0 = null;
        //    int LPIHouduX = b[1] + 100;
        //    LPIHouduY = new int[2];
        //    Mat maskRes =/* null;//*/ new Mat(gray.Rows + 2, gray.Cols + 2, MatType.CV_8UC1);
        //    Mat result1 = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5), 255, ThresholdTypes.Binary);
        //    //if (showMat)
        //    //{
        //    //    Cv2.ImWrite(@"C:\Users\54434\Desktop\FanghanLPI0.png", result1);
        //    //}
        //    LPIHouduY[0] = tonghouY[1];
        //    for (int i = LPIHouduY[0] - 120 - Math.Abs(tonghouY[1] - tonghouY[0]); i < LPIHouduY[0] - 50; i++)
        //    {
        //        if (i>0 && result1.At<byte>(i, LPIHouduX) == 0)
        //        {
        //            Mat mask1 = new Mat(gray.Rows + 2, gray.Cols + 2, MatType.CV_8UC1);
        //            Mat temp = ~result1;
        //            //Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3/*1*/, 3));
        //            //Cv2.Dilate(temp, temp, se);
        //            if (Cv2.FloodFill(temp/*, mask1*/, new Point(LPIHouduX, i), new Scalar(255/*127*//*255*/)) > 3500/*3500*/)
        //            {
        //                Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(/*7*/5/*3*//*1*/, 3));
        //                Cv2.Dilate(temp, temp, se);
        //                Cv2.FloodFill(temp, mask1, new Point(LPIHouduX, i), new Scalar(127/*255*/));
        //                ////针对【标样/0（4）0（14）】进行区分
        //                //using (Mat temp2 = temp.Clone())
        //                //{
        //                //    Mat mask2 = new Mat(gray.Rows + 2, gray.Cols + 2, MatType.CV_8UC1);
        //                //    Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3/*1*/, 3));
        //                //    Cv2.Dilate(temp2, temp2, se);
        //                //    if (Cv2.FloodFill(temp2, mask2, new Point(LPIHouduX, i), new Scalar(127/*255*/)))
        //                //    {
        //                //    }
        //                //}

        //                thresh2_0 = temp.Clone();
        //                //Cv2.ImWrite(@"C:\Users\54434\Desktop\thresh2_0.png", temp);
        //                maskRes = mask1.Clone();
        //                LPIHouduY[1] = i;
        //                break;
        //            }
        //        }
        //    }

        //    if (LPIHouduY[1] == 0)
        //    {
        //        if (showMat)
        //        {
        //            maskRes = FanghanLPIForMeiKaiKou(gray, tonghouY, b, fanghanhouY, out LPIHouduY, out thresh2_0, ++a, true);
        //        }
        //        else
        //            maskRes = FanghanLPIForMeiKaiKou(gray, tonghouY, b, fanghanhouY, out LPIHouduY, out thresh2_0, ++a);
        //    }
        //    else if (showMat)
        //    {
        //        int LPIHouduY_1 = LPIHouduY[1];//防止圆球的影响
        //        float result1Value = BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5);// + 5;
        //        int valueLoop = 0;// LPIHouduY[0] - 50
        //        while (++valueLoop < 15/*12*/ && LPIHouduY_1 == LPIHouduY[1])
        //        {
        //            //valueLoop += 1;
        //            result1 = gray.Threshold(result1Value + valueLoop, 255, ThresholdTypes.Binary);
        //            for (int i = LPIHouduY_1 + 20/*15*/; i < LPIHouduY_1 + 75/*60*//*100*//*50*/; i++)
        //            {
        //                if (i > 0 && result1.At<byte>(i, LPIHouduX) == 0)
        //                {
        //                    Mat mask2 = new Mat(gray.Rows + 2, gray.Cols + 2, MatType.CV_8UC1);
        //                    Mat temp = ~result1;
        //                    if (Cv2.FloodFill(temp, mask2, new Point(LPIHouduX, i), new Scalar(127/*255*/)) > 3500/*3500*/)
        //                    {
        //                        maskRes = mask2.Clone();
        //                        //Cv2.ImWrite(@"C:\Users\54434\Desktop\FanghanLPI2.png", result1);
        //                        LPIHouduY[1] = i;
        //                        break;
        //                    }
        //                }
        //            }
        //        }
        //        //Cv2.ImWrite(@"C:\Users\54434\Desktop\FanghanLPI3.png", result1);
        //    }
        //    return maskRes;
        //}

        /// <summary>
        /// 防焊 没有开口 Undercut
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="offsetX"></param>
        /// <param name="LPIHouY"></param>
        /// <param name="undercutX"></param>
        /// <param name="i"></param>
        public void FanghanUndercutForMeiKaiKou(Mat gray, int[] tonghouY, int[] b, int[] offsetX, int[] LPIHouY, out int undercutX, int i = 0)
        {
            int tempj = -1;
            int tempj_2 = -1;
            undercutX = 0;
            Mat filter = new Mat();
            PointEnhancement(gray, out filter);

            //Cv2.ImWrite(@"C:\Users\54434\Desktop\切片temp\防焊 - 测试图片 另一批\防焊 - 测试图片\undercut沒有開口\1 (2)_4.JPG", filter);

            Mat newGray = new Mat();
            Cv2.GaussianBlur(filter, newGray, new Size(/*7, 7*/15, 15), 5, 5);
            //Cv2.ImWrite(@"C:\Users\zyh\Desktop\newGray.png", newGray);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\切片temp\防焊 - 测试图片 另一批\防焊 - 测试图片\undercut沒有開口\1 (17)_5.JPG", newGray);

            Mat threshEdge_1 = newGray.Threshold(BinaryTools.CalcSuitableValueForUnderCut(gray) - 15/*15*/ + (i * 5), 255, ThresholdTypes.BinaryInv);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray3__0.png", threshEdge_1);
            // Cv2.ImWrite(@"C:\Users\54434\Desktop\切片temp\防焊 - 测试图片 另一批\防焊 - 测试图片\undercut沒有開口\1 (17)_6_1_1.JPG", threshEdge_1);
            Mat result = threshEdge_1.Canny(0, 255);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\切片temp\防焊 - 测试图片 另一批\防焊 - 测试图片\undercut沒有開口\1 (17)_6_1.JPG", result * 255);

            result = BinaryTools.DebrisRemoval_New_1(result, 200);
            ////Cv2.ImWrite(@"C:\Users\zyh\Desktop\result1.png", result * 255);
            ////Cv2.ImWrite(@"C:\Users\54434\Desktop\切片temp\防焊 - 测试图片 另一批\防焊 - 测试图片\undercut沒有開口\1 (17)_6.JPG", result * 255);
            //int thresholdValue = (int)BinaryTools.CalcSuitableValueForUnderCut(gray) + 5;// 73;// (int)BinaryTools.CalcSuitableValueForUnderCut(gray) - 15 + (i * 5) + 5;//73
            //Mat threshEdge_2 = newGray.Threshold(thresholdValue/*BinaryTools.CalcSuitableValueForUnderCut(gray) - 15 + (i * 5) + 5*/, 255, ThresholdTypes.BinaryInv);
            //Mat result_2 = threshEdge_2.Canny(0, 255);
            //result_2 = BinaryTools.DebrisRemoval_New_1(result_2, 200);
            ////Cv2.ImWrite(@"C:\Users\zyh\Desktop\2.png", result_2 * 255);
            ////Cv2.ImWrite(@"C:\Users\54434\Desktop\切片temp\防焊 - 测试图片 另一批\防焊 - 测试图片\undercut沒有開口\1 (17)_7.JPG", result_2 * 255);

            if (true && i == 0)
            {
            int thresholdValue = (int)BinaryTools.CalcSuitableValueForUnderCut(gray) + 5;//(int)BinaryTools.CalcSuitableValueForUnderCut(gray) - 15 + (i * 5) + 5;//73
            Mat threshEdge_2 = newGray.Threshold(thresholdValue/*BinaryTools.CalcSuitableValueForUnderCut(gray) - 15 + (i * 5) + 5*/, 255, ThresholdTypes.BinaryInv);
            Mat result_2 = threshEdge_2.Canny(0, 255);
            result_2 = BinaryTools.DebrisRemoval_New_1(result_2, 200);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\result1.png", result * 255);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\result2.png", result_2 * 255);
            int tempRange = (offsetX[0] - 300) <= 0 ? 1 : offsetX[0] - 300;
            //想左找
            //for (int j = offsetX[0] + 10; j > tempRange; j--)
            //向右找
            for (int j = tempRange; j < offsetX[0]; j++)
            {

                double v = new Mat(result, new Rect(j, tonghouY[1] - 15, 1, 5/*3*//*5*/)).Sum().Val0;
                double v_2 = new Mat(result_2, new Rect(j, tonghouY[1] - 15, 1, 5/*3*//*5*/)).Sum().Val0;
                //byte v = result.Get<byte>((tonghouY[1] + tonghouY[0]) / 2, j);
                //byte v_2 = result_2.Get<byte>((tonghouY[1] + tonghouY[0]) / 2, j);

                if (v_2 > 0)
                {
                    tempj_2 = j;
                    undercutX = j;
                    break;
                }

                if (v > 0)
                {
                    tempj = j;
                    //if (Cv2.FloodFill(result, new Point(j, (tonghouY[1] + tonghouY[0]) / 2), new Scalar(255)) > 100)
                    {
                        undercutX = j;
                        //undercutX = Tools.GetLeftPoint(new Point(j, (tonghouY[1] + tonghouY[0]) / 2), result).X;
                        break;
                    }
                }
            }
            }

            int thresholdValue0 = (int)BinaryTools.CalcSuitableValueForUnderCut(gray) - 15 + (i * 5) + 5;//73

            if (true || undercutX == 0 /*|| (undercutX > 0 && offsetX[0] - undercutX > 100)*/ || tempj_2 < tempj/*undercutX <= 15*/)
            {
                //int thresholdValue = (int)BinaryTools.CalcSuitableValueForUnderCut(gray) - 15 + (i * 5) + 5;//73
                Mat threshEdge_2 = newGray.Threshold(thresholdValue0/*thresholdValue*//*BinaryTools.CalcSuitableValueForUnderCut(gray) - 15 + (i * 5) + 5*/, 255, ThresholdTypes.BinaryInv);
                Mat result_2 = threshEdge_2.Canny(0, 255);
                result_2 = BinaryTools.DebrisRemoval_New_1(result_2, 200);
                int tempRange = (offsetX[0] - 300) <= 0 ? 1 : offsetX[0] - 300;
                //想左找
                //for (int j = offsetX[0] + 10; j > tempRange; j--)
                //向右找
                for (int j = tempRange; j < offsetX[0]; j++)
                {

                    double v = new Mat(result, new Rect(j, tonghouY[1] - 15, 1, 5/*3*//*5*/)).Sum().Val0;
                    double v_2 = new Mat(result_2, new Rect(j, tonghouY[1] - 15, 1, 5/*3*//*5*/)).Sum().Val0;
                    //byte v = result.Get<byte>((tonghouY[1] + tonghouY[0]) / 2, j);
                    //byte v_2 = result_2.Get<byte>((tonghouY[1] + tonghouY[0]) / 2, j);

                    if (v_2 > 0)
                    {
                        if (undercutX == 0 || j - undercutX > 50)
                        {
                            tempj_2 = j;
                            undercutX = j;
                        }
                        break;
                    }

                    if (v > 0)
                    {
                        tempj = j;
                        //if (Cv2.FloodFill(result, new Point(j, (tonghouY[1] + tonghouY[0]) / 2), new Scalar(255)) > 100)
                        {
                            undercutX = j;
                            //undercutX = Tools.GetLeftPoint(new Point(j, (tonghouY[1] + tonghouY[0]) / 2), result).X;
                            break;
                        }
                    }
                }
            }
            //{
            //    int thresholdValue = (int)BinaryTools.CalcSuitableValueForUnderCut(gray) - 15 + (i * 5) + 5;//73
            //    Mat threshEdge_2 = newGray.Threshold(thresholdValue/*BinaryTools.CalcSuitableValueForUnderCut(gray) - 15 + (i * 5) + 5*/, 255, ThresholdTypes.BinaryInv);
            //    Mat result_2 = threshEdge_2.Canny(0, 255);
            //    result_2 = BinaryTools.DebrisRemoval_New_1(result_2, 200);
            //    int tempRange = (offsetX[0] - 300) <= 0 ? 1 : offsetX[0] - 300;
            //    //想左找
            //    //for (int j = offsetX[0] + 10; j > tempRange; j--)
            //    //向右找
            //    for (int j = tempRange; j < offsetX[0]; j++)
            //    {

            //        double v = new Mat(result, new Rect(j, tonghouY[1] - 15, 1, 7/*3*//*5*/)).Sum().Val0;
            //        double v_2 = new Mat(result_2, new Rect(j, tonghouY[1] - 15, 1, 7/*3*//*5*/)).Sum().Val0;
            //        //byte v = result.Get<byte>((tonghouY[1] + tonghouY[0]) / 2, j);
            //        //byte v_2 = result_2.Get<byte>((tonghouY[1] + tonghouY[0]) / 2, j);

            //        if (v_2 > 0)
            //        {
            //            tempj_2 = j;
            //            undercutX = j;
            //            break;
            //        }

            //        if (v > 0)
            //        {
            //            tempj = j;
            //            //if (Cv2.FloodFill(result, new Point(j, (tonghouY[1] + tonghouY[0]) / 2), new Scalar(255)) > 100)
            //            {
            //                undercutX = j;
            //                //undercutX = Tools.GetLeftPoint(new Point(j, (tonghouY[1] + tonghouY[0]) / 2), result).X;
            //                break;
            //            }
            //        }
            //    }
            //}

            if (i > 15)
            {
                //undercutX = (tempj == -1) ? offsetX[0] - 25 : tempj;
                //undercutX = offsetX[0] - 25;
            }
            else
            {
                if (undercutX == 0 /*|| (undercutX > 0 && offsetX[0] - undercutX > 100)*/ || tempj_2 < tempj)
                {
                    FanghanUndercutForMeiKaiKou(gray, tonghouY, b, offsetX, LPIHouY, out undercutX, ++i);
                }
                else
                {
                    FanghanUndercutForMeiKaiKou_ACC(gray, tonghouY, b, offsetX, LPIHouY, out undercutX, undercutX, undercutX, thresholdValue0 - 5/* - 5*//*thresholdValue0 + 5*//*, ++i*/);
                    //undercutX -= 5;
                    ////undercutX = (undercutX + tempj) / 2 - 5;
                }
            }
        }

        /// <summary>
        /// 防焊 没有开口 Undercut 为了精确找到左端点进行方法调试
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="offsetX"></param>
        /// <param name="LPIHouY"></param>
        /// <param name="undercutX"></param>
        /// <param name="i"></param>
        public void FanghanUndercutForMeiKaiKou_ACC(Mat gray, int[] tonghouY, int[] b, int[] offsetX, int[] LPIHouY, out int undercutX, int undercutX0, int undercutXOld, int /*threshEdge_1*/thresholdValue01/*, int i = 0*/)
        {
            //int tempj = -1;
            int tempj_2 = -1;
            undercutX = undercutX0;
            Mat filter = new Mat();
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray0.png", gray);
            PointEnhancement(gray, out filter);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray1.png", filter);

            //Mat newGray = new Mat();
            //Cv2.GaussianBlur(filter, newGray, new Size(/*7, 7*/15, 15), 5, 5);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray2.png", newGray);

            int thresholdValue = (int)BinaryTools.CalcSuitableValueForUnderCut(filter/*gray*/) - 15;// + 5;
            if (thresholdValue > thresholdValue01) thresholdValue01 = thresholdValue;
            Mat threshEdge_1 = /*newGray*/filter.Threshold(thresholdValue01, 255, ThresholdTypes.BinaryInv);// filter.Threshold(0, 255, ThresholdTypes.Otsu);
            //Mat threshEdge_1 = newGray.Threshold(thresholdValue01, 255, ThresholdTypes.BinaryInv);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray3.png", threshEdge_1);
           // Mat result = threshEdge_1.Canny(0, 255);
            //result = BinaryTools.DebrisRemoval_New_1(result, 20);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\result1.png", result * 255);

            //Mat threshEdge_2 = newGray.Threshold(thresholdValue0, 255, ThresholdTypes.BinaryInv);
            //Mat result_2 = threshEdge_2.Canny(0, 255);
            //result_2 = BinaryTools.DebrisRemoval_New_1(result_2, 200);
            int tempRange = (undercutX0 - 30) <= 0 ? 1 : undercutX0 - 30;
            //int tempRange = (offsetX[0] - 300) <= 0 ? 1 : offsetX[0] - 300;
            //想左找
            bool foundLeftCut = false;
            for (int j = undercutX0 - 1; j > tempRange; j--)
            ////向右找
            //for (int j = tempRange; j < offsetX[0]; j++)
            {
                double v = new Mat(threshEdge_1/*result*/, new Rect(j, tonghouY[1] - 20/*15*/, 3/*3*//*1*/, 20/*15*//*5*//*3*//*5*/)).Sum().Val0;
                //double v_2 = new Mat(result_2, new Rect(j, tonghouY[1] - 15, 1, 5/*3*//*5*/)).Sum().Val0;

                if (v/*v_2*/ > 0)
                {
                    foundLeftCut = true;
                    //if (undercutX == 0 || j - undercutX > 50)
                    //{
                    //    tempj_2 = j;
                    //    undercutX = j;
                    //}
                }
                else
                {
                    if (foundLeftCut)
                    {
                        tempj_2 = j;
                        undercutX = j;
                    }
                    break;
                }
                //if (v > 0)
                //{
                //    tempj = j;
                //    undercutX = j;
                //    break;
                //}
            }

            //if (i > 15)
            //{
            //    //undercutX = (tempj == -1) ? offsetX[0] - 25 : tempj;
            //    //undercutX = offsetX[0] - 25;
            //}
            //else
            {
                if (foundLeftCut)//undercutX == 0 /*|| (undercutX > 0 && offsetX[0] - undercutX > 100)*/ || tempj_2 < tempj)
                {
                    if (undercutX == undercutX0)
                        FanghanUndercutForMeiKaiKou_ACC(gray, tonghouY, b, offsetX, LPIHouY, out undercutX, tempRange, undercutXOld, thresholdValue01/*thresholdValue0*//* + 5*//*, ++i*/);
                    //else
                    //    FanghanUndercutForMeiKaiKou_ACC(gray, tonghouY, b, offsetX, LPIHouY, out undercutX, undercutX, thresholdValue01/*thresholdValue0*/ + 5/*, ++i*/);
                    else
                    {
                        //安全距離
                        ////undercutX[1] = offsetX[0];
                        //int[] anquanjuliX = { b[1], undercutX[0] < undercutX[1] ? undercutX[0] : undercutX[1] };
                        undercutX = Math.Max(0, undercutX - 5);// 1;// 5;
                        int[] anquanjuliX = { b[1], undercutX < offsetX[0] ? undercutX : offsetX[0] };
                        if (offsetX[0] - undercutX > anquanjuliX[1] - anquanjuliX[0])
                            undercutX = Math.Max(0, undercutXOld - 25);// 5;//严重安全距离不能过长

                    }
                }
                else
                {
                    if (thresholdValue01 < 100)
                        FanghanUndercutForMeiKaiKou_ACC(gray, tonghouY, b, offsetX, LPIHouY, out undercutX, undercutX, undercutXOld, thresholdValue01/*thresholdValue0*/ + 5/*, ++i*/);
                    else
                    {
                        //安全距離
                        ////undercutX[1] = offsetX[0];
                        //int[] anquanjuliX = { b[1], undercutX[0] < undercutX[1] ? undercutX[0] : undercutX[1] };
                        undercutX = Math.Max(0, undercutX - 5);// 1;// 5;
                        int[] anquanjuliX = { b[1], undercutX < offsetX[0] ? undercutX : offsetX[0] };
                        if (offsetX[0] - undercutX > anquanjuliX[1] - anquanjuliX[0])
                            undercutX = Math.Max(0, undercutXOld - 5);//严重安全距离不能过长

                    }
                    //undercutX = (undercutX + tempj) / 2 - 5;
                }
            }
            Cv2.Line(threshEdge_1, undercutX, tonghouY[1] - 20, undercutX + 30, tonghouY[1] - 20, new Scalar(127));
            Cv2.Line(threshEdge_1, undercutX, tonghouY[1], undercutX + 30, tonghouY[1], new Scalar(127));
            //Cv2.Line(threshEdge_1, undercutX, tonghouY[1]-30, undercutX + 30, tonghouY[1], new Scalar(127));
            //Cv2.Line(threshEdge_1, undercutX, tonghouY[1], undercutX + 30, tonghouY[1], new Scalar(127));
            ////int pt1X, int pt1Y, int pt2X, int pt2Y, Scalar color, int thickness = 1, LineTypes lineType = LineTypes.Link8, int shift = 0)
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray3.png", threshEdge_1);
        }


        /// <summary>
        /// 防焊 没有开口 防焊厚度上端点 以及 Offset 为了精确找到左端点进行方法调试
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="offsetX"></param>
        /// <param name="LPIHouY"></param>
        /// <param name="undercutX"></param>
        /// <param name="i"></param>
        public void FanghanRectForMeiKaiKou_ACC(Mat gray, int[] tonghouY, int[] b, int[] offsetX, int[] LPIHouY, out int undercutX, int undercutX0, int undercutXOld, int /*threshEdge_1*/thresholdValue01/*, int i = 0*/)
        {
            //int tempj = -1;
            int tempj_2 = -1;
            undercutX = undercutX0;
            Mat filter = new Mat();
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray0.png", gray);
            PointEnhancement(gray, out filter);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray1.png", filter);

            //Mat newGray = new Mat();
            //Cv2.GaussianBlur(filter, newGray, new Size(/*7, 7*/15, 15), 5, 5);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray2.png", newGray);

            int thresholdValue = (int)BinaryTools.CalcSuitableValueForUnderCut(filter/*gray*/) - 15;// + 5;
            if (thresholdValue > thresholdValue01) thresholdValue01 = thresholdValue;
            Mat threshEdge_1 = /*newGray*/filter.Threshold(thresholdValue01, 255, ThresholdTypes.BinaryInv);// filter.Threshold(0, 255, ThresholdTypes.Otsu);
                                                                                                            //Mat threshEdge_1 = newGray.Threshold(thresholdValue01, 255, ThresholdTypes.BinaryInv);
                                                                                                            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray3.png", threshEdge_1);
                                                                                                            // Mat result = threshEdge_1.Canny(0, 255);
                                                                                                            //result = BinaryTools.DebrisRemoval_New_1(result, 20);
                                                                                                            //Cv2.ImWrite(@"C:\Users\54434\Desktop\result1.png", result * 255);

            //Mat threshEdge_2 = newGray.Threshold(thresholdValue0, 255, ThresholdTypes.BinaryInv);
            //Mat result_2 = threshEdge_2.Canny(0, 255);
            //result_2 = BinaryTools.DebrisRemoval_New_1(result_2, 200);
            int tempRange = (undercutX0 - 30) <= 0 ? 1 : undercutX0 - 30;
            //int tempRange = (offsetX[0] - 300) <= 0 ? 1 : offsetX[0] - 300;
            //想左找
            bool foundLeftCut = false;
            for (int j = undercutX0 - 1; j > tempRange; j--)
            ////向右找
            //for (int j = tempRange; j < offsetX[0]; j++)
            {
                double v = new Mat(threshEdge_1/*result*/, new Rect(j, tonghouY[1] - 20/*15*/, 3/*3*//*1*/, 20/*15*//*5*//*3*//*5*/)).Sum().Val0;
                //double v_2 = new Mat(result_2, new Rect(j, tonghouY[1] - 15, 1, 5/*3*//*5*/)).Sum().Val0;

                if (v/*v_2*/ > 0)
                {
                    foundLeftCut = true;
                    //if (undercutX == 0 || j - undercutX > 50)
                    //{
                    //    tempj_2 = j;
                    //    undercutX = j;
                    //}
                }
                else
                {
                    if (foundLeftCut)
                    {
                        tempj_2 = j;
                        undercutX = j;
                    }
                    break;
                }
                //if (v > 0)
                //{
                //    tempj = j;
                //    undercutX = j;
                //    break;
                //}
            }

            //if (i > 15)
            //{
            //    //undercutX = (tempj == -1) ? offsetX[0] - 25 : tempj;
            //    //undercutX = offsetX[0] - 25;
            //}
            //else
            {
                if (foundLeftCut)//undercutX == 0 /*|| (undercutX > 0 && offsetX[0] - undercutX > 100)*/ || tempj_2 < tempj)
                {
                    if (undercutX == undercutX0)
                        FanghanUndercutForMeiKaiKou_ACC(gray, tonghouY, b, offsetX, LPIHouY, out undercutX, tempRange, undercutXOld, thresholdValue01/*thresholdValue0*//* + 5*//*, ++i*/);
                    //else
                    //    FanghanUndercutForMeiKaiKou_ACC(gray, tonghouY, b, offsetX, LPIHouY, out undercutX, undercutX, thresholdValue01/*thresholdValue0*/ + 5/*, ++i*/);
                    else
                    {
                        //安全距離
                        ////undercutX[1] = offsetX[0];
                        //int[] anquanjuliX = { b[1], undercutX[0] < undercutX[1] ? undercutX[0] : undercutX[1] };
                        undercutX -= 5;// 1;// 5;
                        int[] anquanjuliX = { b[1], undercutX < offsetX[0] ? undercutX : offsetX[0] };
                        if (offsetX[0] - undercutX > anquanjuliX[1] - anquanjuliX[0])
                            undercutX = undercutXOld - 25;// 5;//严重安全距离不能过长

                    }
                }
                else
                {
                    if (thresholdValue01 < 100)
                        FanghanUndercutForMeiKaiKou_ACC(gray, tonghouY, b, offsetX, LPIHouY, out undercutX, undercutX, undercutXOld, thresholdValue01/*thresholdValue0*/ + 5/*, ++i*/);
                    else
                    {
                        //安全距離
                        ////undercutX[1] = offsetX[0];
                        //int[] anquanjuliX = { b[1], undercutX[0] < undercutX[1] ? undercutX[0] : undercutX[1] };
                        undercutX -= 5;// 1;// 5;
                        int[] anquanjuliX = { b[1], undercutX < offsetX[0] ? undercutX : offsetX[0] };
                        if (offsetX[0] - undercutX > anquanjuliX[1] - anquanjuliX[0])
                            undercutX = undercutXOld - 5;//严重安全距离不能过长

                    }
                    //undercutX = (undercutX + tempj) / 2 - 5;
                }
            }
            Cv2.Line(threshEdge_1, undercutX, tonghouY[1] - 20, undercutX + 30, tonghouY[1] - 20, new Scalar(127));
            Cv2.Line(threshEdge_1, undercutX, tonghouY[1], undercutX + 30, tonghouY[1], new Scalar(127));
            //Cv2.Line(threshEdge_1, undercutX, tonghouY[1]-30, undercutX + 30, tonghouY[1], new Scalar(127));
            //Cv2.Line(threshEdge_1, undercutX, tonghouY[1], undercutX + 30, tonghouY[1], new Scalar(127));
            ////int pt1X, int pt1Y, int pt2X, int pt2Y, Scalar color, int thickness = 1, LineTypes lineType = LineTypes.Link8, int shift = 0)
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray3.png", threshEdge_1);
        }

        #endregion

        #region 开口

        /// <summary>
        /// 防焊 有开口 铜厚
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        public void FanghanTonghouForYouKaiKou_Acc(Mat gray, int tonghouX, out int tonghouY0, int[] y/*, out int[] y, out int[] b*/)
        {
            ////y = new int[2];
            ////b = new int[4];
            tonghouY0 = 0;// new int[2];
            Mat contour = new Mat();
            double T = 0;
            double t = Cv2.Threshold(gray, contour, 0, 255, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(15, 15));
            Mat close = new Mat();
            Cv2.MorphologyEx(contour, close, MorphTypes.Close, seClose);
            Mat result = close.Clone();
            result = result / 255;
            ////计算铜厚
            //int tonghouX = b[1] - 150;
            Mat thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            for (int i = y[0]; i < y[1]; i++)
            {
                Scalar sum = thresh[i, i + 1, tonghouX - 30, tonghouX + 30].Sum();
                if ((int)sum > 30)
                {
                    tonghouY0 = i;
                    break;
                }
            }
            //contour = contour / 255;
            //for (int i = tonghouY[0] + 30; i < contour.Rows; i++)
            //{
            //    Scalar sum = contour[i, i + 1, tonghouX - 30, tonghouX + 30].Sum();
            //    if ((int)sum == 0)
            //    {
            //        tonghouY[1] = i;
            //        break;
            //    }
            //}
        }

        /// <summary>
        /// 防焊 有开口 铜厚
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        public void FanghanTonghouForYouKaiKou(Mat gray, out int[] tonghouY, out int[] y, out int[] b)
        {
            y = new int[2];
            b = new int[4];
            tonghouY = new int[2];
            Mat contour = new Mat();
            double T = 0;
            double t = Cv2.Threshold(gray, contour, 0, 255, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(15, 15));
            Mat close = new Mat();
            Cv2.MorphologyEx(contour, close, MorphTypes.Close, seClose);
            Mat result = close.Clone();
            result = result / 255;
            //ImageShow(result * 255);
            //计算边界
            Scalar sum = new Scalar(0);
            for (int i = 0; i < result.Rows; i++)
            {
                sum = result[i, i + 1, 0, result.Cols].Sum();
                if ((int)sum > 200)
                {
                    y[0] = i - 20;
                    break;
                }
            }
            for (int i = y[0] + 50; i < result.Rows; i++)
            {
                sum = result[i, i + 1, 0, result.Cols].Sum();
                if ((int)sum == 0)
                {
                    y[1] = i;
                    break;
                }
            }
            for (int j = 0; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum > 20)
                {
                    b[0] = j;
                    break;
                }
            }
            for (int j = b[0] + 200; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum == 0)
                {
                    b[1] = j;
                    break;
                }
            }
            for (int j = b[1] + 10; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum > 20)
                {
                    b[2] = j;
                    break;
                }
            }
            if (b[2] - b[1] < 300)
            {
                for (int j = b[2] + 50; j < result.Cols; j++)
                {
                    sum = result[y[0], y[1], j, j + 1].Sum();
                    if ((int)sum == 0)
                    {
                        b[1] = j;
                        break;
                    }
                }
                for (int j = b[1] + 10; j < result.Cols; j++)
                {
                    sum = result[y[0], y[1], j, j + 1].Sum();
                    if ((int)sum > 20)
                    {
                        b[2] = j;
                        break;
                    }
                }
            }
            for (int j = b[2] + 50; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum == 0)
                {
                    b[3] = j;
                    break;
                }
            }
            if (b[3] == 0)
                b[3] = contour.Cols - 1;
            //计算铜厚
            int tonghouX = b[1] - 150;
            Mat thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            for (int i = y[0]; i < y[1]; i++)
            {
                sum = thresh[i, i + 1, tonghouX - 30, tonghouX + 30].Sum();
                if ((int)sum > 30)
                {
                    tonghouY[0] = i;
                    break;
                }
            }
            contour = contour / 255;
            for (int i = tonghouY[0] + 30; i < contour.Rows; i++)
            {
                sum = contour[i, i + 1, tonghouX - 30, tonghouX + 30].Sum();
                if ((int)sum == 0)
                {
                    tonghouY[1] = i;
                    break;
                }
            }
        }

        /// <summary>
        /// 防焊 有开口 厚度
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        /// <param name="tonghouY"></param>
        /// <param name="fanghanhouduY"></param>
        /// <param name="a"></param>
        public void FanghanhouduForYouKaiKou_2(Mat gray, int[] y, int fanghanhouduX, int[] tonghouY, out int fanghanhouduY1, out int minGray, bool isLeft)
        {
            int fanghanhouduY_0 = tonghouY[0];
            int fanghanX1 = Math.Max(0, fanghanhouduX - 150);
            int fanghanX2 = Math.Min(gray.Cols - 1, fanghanhouduX + 150);
            int fanghanTop = fanghanhouduY_0 - 150/*100*/;
            int marginTop = 150;
            if (fanghanTop < 0)
            {
                fanghanTop = 0;
                marginTop = fanghanhouduY_0 - 1;
            }

            Mat grayRect = gray[fanghanTop, fanghanhouduY_0 - 50, fanghanX1, fanghanX2];
            FanghanhouduForYouKaiKou/*_00*/(grayRect/*gray*/, y, marginTop/*150*//*fanghanhouduX*/, tonghouY, out fanghanhouduY1, out minGray);


            int fanghanhouduY1__2 = fanghanhouduY1;
            int minGray__2 = minGray;
            fanghanX1 += 140;// 145;
            fanghanX2 -= 140;// 145;
            grayRect = gray[fanghanTop, fanghanhouduY_0 - 20/*50*/, fanghanX1, fanghanX2];

            int fanghanhouduY1__2_bottom;
            FanghanhouduForYouKaiKou_ACC(grayRect, y, marginTop, fanghanhouduY1 - (isLeft ? 8/*5*/ : 1), out fanghanhouduY1__2, out fanghanhouduY1__2_bottom, out minGray__2);

            if (true && (Math.Abs(fanghanhouduY1 - fanghanhouduY1__2) < 16/*11*//*<-10*//*20*//*10*/
                || (!isLeft && Math.Abs(fanghanhouduY1 - fanghanhouduY1__2) < 25/*20*/)))
                fanghanhouduY1 = fanghanhouduY1__2/*fanghanhouduY1__2_bottom*//*fanghanhouduY1__2*/ + fanghanTop;// +5;
            else
                fanghanhouduY1 = fanghanhouduY1 + fanghanTop;
        }
        /// <summary>
        /// 防焊 有开口 厚度 精确计算
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        /// <param name="tonghouY"></param>
        /// <param name="fanghanhouduY"></param>
        /// <param name="a"></param>
        private void FanghanhouduForYouKaiKou_ACC(Mat gray, int[] y, int fanghanhouduX, int fanghanhouduY1__0, out int fanghanhouduY1, out int fanghanhouduY1Bottom, out int minGray, int a = 0)
        {
            minGray = 300 * 255;
            int fanghanhouduY1__noSharp = -1;// fanghanhouduY1;
            {
                int minRowIndex = 0; int colEnd = gray.Cols - 1; int curGray; List<int> curGrayList = new List<int>();
                fanghanhouduY1Bottom = 0;
                for (int i = Math.Max(0, fanghanhouduY1__0 - 0/*1*//*5*//*10*/); i < Math.Min(fanghanhouduY1__0 + 30/*25*/, gray.Rows) - 5; i++)
                {
                    curGray = this.FanghanhouduForAreaMin(gray, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                    curGrayList.Add(curGray);
                    if (curGray < minGray)
                    {
                        minRowIndex = i;
                        fanghanhouduY1Bottom = i;
                        minGray = curGray;
                    }
                }
                for (int i = minRowIndex - Math.Max(0, fanghanhouduY1__0 - 0/*1*//*5*//*10*/) + 2; i < curGrayList.Count; i += 2)
                {
                    if (Math.Abs(curGrayList[i] - minGray) < 10/*100*/)
                    {
                        minRowIndex += 1;
                        fanghanhouduY1Bottom += 2;
                    }
                }
                fanghanhouduY1__noSharp = minRowIndex;// 84;// 72;// minRowIndex;
            }
            {
                //锐化
                //Mat left_small_sharp = BinaryTools.BlurMaskFunction(left_small).CvtColor(ColorConversionCodes.BGRA2GRAY);
                gray = BinaryTools.BlurMaskFunction(gray/*grayRect*/, 4f * 3.14f, 1, 10f).CvtColor(ColorConversionCodes.BGRA2GRAY);
                int minRowIndex = 0; int colEnd = gray.Cols - 1; int curGray; List<int> curGrayList = new List<int>();
                fanghanhouduY1Bottom = 0;
                for (int i = Math.Max(0, fanghanhouduY1__0 - 0/*1*//*5*//*10*/); i < Math.Min(fanghanhouduY1__0 + 30/*25*/, gray.Rows) - 5; i++)
                {
                    curGray = this.FanghanhouduForAreaMin(gray, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                    curGrayList.Add(curGray);
                    if (curGray < minGray)
                    {
                        minRowIndex = i;
                        fanghanhouduY1Bottom = i;
                        minGray = curGray;
                    }
                }
                for (int i = minRowIndex - Math.Max(0, fanghanhouduY1__0 - 0/*1*//*5*//*10*/) + 2; i < curGrayList.Count; i += 2)
                {
                    if (Math.Abs(curGrayList[i] - minGray) < 10/*100*/)
                    {
                        minRowIndex += 1;
                        fanghanhouduY1Bottom += 2;
                    }
                }
                //Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
                ////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
                fanghanhouduY1 = minRowIndex;// 84;// 72;// minRowIndex;
            }
            if (Math.Abs(fanghanhouduY1__noSharp - fanghanhouduY1) < 7/* <<7 8*//* << 6 *//*5*/)
            {
                fanghanhouduY1 = fanghanhouduY1__noSharp;
            }
            else
                Console.WriteLine("fanghanhouduY1 far away from fanghanhouduY1__noSharp.");
        }
        /// <summary>
        /// 防焊 有开口 厚度
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        /// <param name="tonghouY"></param>
        /// <param name="fanghanhouduY"></param>
        /// <param name="a"></param>
        private void FanghanhouduForYouKaiKou_00(Mat gray, int[] y, int fanghanhouduX, int[] tonghouY, out int fanghanhouduY1, out int minGray, int a = 0)
        {
            /*int fanghanhouduX = 150; */
            fanghanhouduY1 = -1;
            Mat thresh = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5), 255, ThresholdTypes.Binary);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", thresh);
            for (int i = 0; i < 100; i++)
            {
                if (thresh.At<byte>(i, fanghanhouduX) == 0 && Cv2.FloodFill(thresh, new Point(fanghanhouduX, i), new Scalar(255)) > 300)
                {
                    fanghanhouduY1 = i;
                    break;
                }
            }
            minGray = 300 * 255;
            if (fanghanhouduY1 == -1)
                FanghanhouduForYouKaiKou_00(gray, y, fanghanhouduX, tonghouY, out fanghanhouduY1, out minGray, ++a);
            //else
            //{//计算数值的地方
            // //Console.WriteLine("fanghanhouduY1_0:" + fanghanhouduY1);
            //    /*int minGray = 300*255; */
            //    int minRowIndex = 0; int colEnd = thresh.Cols - 1; int curGray;
            //    for (int i = 6/*1*/; i < 95; i++)
            //    {
            //        curGray = this.FanghanhouduForAreaMin(gray, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
            //        if (curGray < minGray)
            //        {
            //            minRowIndex = i;
            //            minGray = curGray;
            //        }
            //    }
            //    //Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
            //    ////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
            //    fanghanhouduY1 = minRowIndex;
            //}
        }

        /// <summary>
        /// 防焊 有开口 厚度
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        /// <param name="tonghouY"></param>
        /// <param name="fanghanhouduY"></param>
        /// <param name="a"></param>
        private void FanghanhouduForYouKaiKou(Mat gray, int[] y, int fanghanhouduX, int[] tonghouY, out int fanghanhouduY1, out int minGray, int a = 0)
        {
            /*int fanghanhouduX = 150; */fanghanhouduY1 = -1;
            //Mat thresh = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5), 255, ThresholdTypes.Binary);
            ////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", thresh);
            //for (int i = 0; i < 100; i++)
            //{
            //    if (thresh.At<byte>(i, fanghanhouduX) == 0 && Cv2.FloodFill(thresh, new Point(fanghanhouduX, i), new Scalar(255)) > 300)
            //    {
            //        fanghanhouduY1 = i;
            //        break;
            //    }
            //}
            minGray = 300 * 255;
            //if (fanghanhouduY1 == -1)
            //    FanghanhouduForYouKaiKou(gray, y, fanghanhouduX, tonghouY, out fanghanhouduY1, out minGray, ++a);
            //else
            {//计算数值的地方
                //Console.WriteLine("fanghanhouduY1_0:" + fanghanhouduY1);
                /*int minGray = 300*255; */int minRowIndex = 0; int colEnd = gray.Cols - 1; int curGray;
                for (int i = 6/*1*/; i < 95; i++)
                {
                    curGray = this.FanghanhouduForAreaMin(gray, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                    if (curGray < minGray)
                    {
                        minRowIndex = i;
                        minGray = curGray;
                    }
                }
                //Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
                ////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
                fanghanhouduY1 = minRowIndex;
            }
        }
        /// <summary>
        /// 获取灰度值最低的一条横线
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="fanghanhouduY1"></param>
        public void FanghanhouduRightForYouKaiKou(Mat gray, out int fanghanhouduY1)
        {//计算数值的地方
            int minGray = gray.Cols/*300*/ * 255;
            int minRowIndex = 0; int colEnd = gray.Cols - 1; int curGray;
            for (int i = /*6*/6; i < 95; i++)
            {
                curGray = this.FanghanhouduForAreaMin(gray, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                if (curGray < minGray)
                {
                    minRowIndex = i;
                    minGray = curGray;
                }
            }
            fanghanhouduY1 = minRowIndex;
        }
        //获取当前行附件最暗的总和
        private int FanghanhouduForAreaMin(Mat gray, int rowIndex)
        {
            int areaMin = 0;
            for (int i = 0; i < gray.Cols; i++)
            {
                int colMin = 255;
                for (int j = rowIndex - 5/*Math.Max(0, rowIndex - 5)*/; j < rowIndex + 5; j++)
                    if (gray.At<byte>(j, i) < colMin) colMin = gray.At<byte>(j, i);
                areaMin += colMin;
            }
            return areaMin;
        }

        /// <summary>
        /// 防焊 有开口 offset
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="offsetX"></param>
        /// <param name="i"></param>
        public void FanghanOffsetForYouKaiKou_Acc(Mat gray0, int[] tonghouY, int[] b, int[] fanghanhouY, int offsetY, int offsetX0_0, out int offsetX0)
        {
            int offsetY1 = Math.Max(0, fanghanhouY[1] - 50);
            int offsetY2 = Math.Min(gray0.Rows - 1, tonghouY[1] + 50);
            int offsetLeft = b[1] + 5;
            Mat gray = gray0[offsetY1, offsetY2, offsetLeft, b[2] - 5];
            int colStart = offsetX0_0 - 10 - offsetLeft;
            int colEnd = offsetX0_0 + 20/*10*/ - offsetLeft;

            int minGray = 300 * 255; int minColIndex = 0; int rowStart = offsetY - 10 - offsetY1; int rowEnd = offsetY + 10 - offsetY1;
            List<int> curgrayList = new List<int>();
            List<int> minareaList_k = new List<int>();
            List<int> minareaList_v = new List<int>();
            for (int i = colStart; i < colEnd; i++)
            {
                curgrayList.Add(this.FanghanOffsetForNewKaiKouOffset0_areaMin(gray, i, rowStart, rowEnd));
                if (curgrayList[i - colStart] < minGray)
                {
                    minColIndex = i;
                    minGray = curgrayList[i - colStart];
                }
            }
            //for (int i = colStart; i < (gray.Cols + colStart) / 2; i++)
            //{
            //    if (i > colStart + 10 && i < (gray.Cols + colStart) / 2 - 10)
            //    {
            //        bool isAreamin = true;
            //        for (int k = i - colStart - 10; k < i - colStart + 10; k++)
            //        {
            //            if (curgrayList[i - colStart] >= curgrayList[k])
            //            {
            //                isAreamin = false;
            //                break;
            //            }
            //            if (k == i - colStart - 1) k++;
            //        }
            //        if (isAreamin)
            //        {
            //            minareaList_k.Add(i);
            //            minareaList_v.Add(curgrayList[i - colStart]);
            //        }
            //    }

            //}
            ////Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
            //////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
            ////下面为计算极小值，从计算极小值中的序列中选取，替换极大值
            ////minareaList.Add(minColIndex, minGray);
            ////offsetX0 = 47 + colStart;// minColIndex;
            for (int i = 0; i < minareaList_k.Count; i++)
            {
                if (Math.Abs(minGray - minareaList_v[i]) < 120)
                {
                    minColIndex = minareaList_k[i];
                    break;
                }
            }
            offsetX0 = minColIndex;

            offsetX0 = offsetX0 + offsetLeft;

        }

        /// <summary>
        /// 防焊 有开口 offset
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="offsetX"></param>
        /// <param name="i"></param>
        public void FanghanOffsetForYouKaiKou(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, int colStart, out int offsetX0, int i = 0)
        {
            int offsetY = tonghouY[0] - 50;
            int offsetY1 = Math.Max(0, fanghanhouY[1]/*offsetY*/ - 50);
            int offsetY2 = Math.Min(gray.Rows - 1, tonghouY[1] + 50);
            int offsetLeft = b[1] + 5;
            if (offsetLeft >= b[2] - 5)
            {
                offsetLeft = b[2] - 5 - 1;
            }
            Mat grayRect = gray[offsetY1, offsetY2, offsetLeft, b[2] - 5];
            this.FanghanOffsetForNewKaiKouOffset0(grayRect, colStart, out offsetX0);
            offsetX0 = offsetX0 + offsetLeft;

            ////二值化
            //Mat threshEdge = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (i * 5), 255, ThresholdTypes.BinaryInv);
            ////去碎屑
            //threshEdge = ~BinaryTools.DebrisRemoval_New(threshEdge.CvtColor(ColorConversionCodes.GRAY2BGRA), 250).CvtColor(ColorConversionCodes.BGRA2GRAY);
            //for (int j = b[2] - 55; j > 0; j--)
            //{
            //    if (threshEdge.At<byte>(offsetY + 45, j) == 0)
            //    {
            //        Mat temp = ~threshEdge;
            //        if (Cv2.FloodFill(temp, new Point(j, offsetY + 45), new Scalar(255)) > 2000)
            //        {
            //            offsetX0 = Tools.GetLeftOrRightPoint(new Point(j, offsetY + 45), threshEdge, 2).X;
            //            break;
            //        }
            //    }
            //}
            //if (i  <20 && (offsetX0 <= 0 || Math.Abs(b[2]/*offsetX_1*/ - offsetX0) > 800))
            //    FanghanOffsetForYouKaiKou(gray, tonghouY, b, fanghanhouY, out offsetX0, ++i);
        }
        public void FanghanKaikouForNewKaiKou(Mat gray, int colStart, int colEnd, int fanghankaikouYTopCenter, out int kaikouX1)
        {//计算数值的地方
         ////Console.WriteLine("fanghanhouduY1_0:" + fanghanhouduY1);
         //   offsetX0 = -1;
         //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray.png", gray);
            int minGray = (colEnd-colStart)/*300*/ * 255; int minColIndex = 0; int rowStart = Math.Max(fanghankaikouYTopCenter-20,0)/*50*/; int rowEnd = Math.Min(fanghankaikouYTopCenter+80, gray.Rows-1)/*130*//*gray.Rows - 50*/;// int curGray;
            List<int> curgrayList = new List<int>();
            List<int> minareaList_k = new List<int>();
            List<int> minareaList_v = new List<int>();
            for (int i = colEnd/*(gray.Cols + colStart) / 2 *//*gray.Cols - 50*/; i > colStart/*6*//*1*/; i--)
                //for (int i = colStart/*6*//*1*/; i < colEnd/*(gray.Cols + colStart) / 2 *//*gray.Cols - 50*/; i++)
            {
                curgrayList.Add(this.FanghanOffsetForNewKaiKouOffset0_areaMin(gray, i, rowStart, rowEnd));
                if (curgrayList[colEnd - i/*i - colStart*/] < minGray)
                {
                    minColIndex = i;
                    minGray = curgrayList[colEnd - i/*i - colStart*/];
                }
            }
            for (int i = colEnd/*(gray.Cols + colStart) / 2*/ /*gray.Cols - 50*/; i > colStart/*6*//*1*/; i--)
            {
                if (i > colStart + 10 && i < colEnd/*(gray.Cols + colStart) / 2*/ - 10)
                {
                    bool isAreamin = true;
                    for (int k = colEnd - i/*i - colStart*/ + 10/*10*/; k > colEnd - i/*i - colStart*/ - 10/*10*/; k--)
                    {
                        if (curgrayList[colEnd - i/*i - colStart*/] >= curgrayList[k])
                        {
                            isAreamin = false;
                            break;
                        }
                        if (k == colEnd - i/*i - colStart*/ + 1) k--;
                    }
                    if (isAreamin)
                    {
                        minareaList_k.Add(i);
                        minareaList_v.Add(curgrayList[colEnd - i/*i - colStart*/]);
                    }
                }

            }
            //Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
            ////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
            //下面为计算极小值，从计算极小值中的序列中选取，替换极大值
            //minareaList.Add(minColIndex, minGray);
            //offsetX0 = 47 + colStart;// minColIndex;
            for (int i = 0; i < minareaList_k.Count; i++)
            {
                if (Math.Abs(minGray - minareaList_v[i]) < 300/*120*/)
                {
                    minColIndex = minareaList_k[i];
                    break;
                }
            }
            kaikouX1 = minColIndex;
            //
        }
        public void FanghanOffsetForNewKaiKouOffset0(Mat gray, int colStart, out int offsetX0)
        {//计算数值的地方
         ////Console.WriteLine("fanghanhouduY1_0:" + fanghanhouduY1);
         //   offsetX0 = -1;
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray.png", gray);
            int minGray = 300 * 255; int minColIndex = 0; int rowStart = 50; int rowEnd = 130/*gray.Rows - 50*/;// int curGray;
            List<int> curgrayList = new List<int>();
            List<int> minareaList_k = new List<int>();
            List<int> minareaList_v = new List<int>();
            for (int i = colStart/*6*//*1*/; i < (gray.Cols+ colStart)/2 /*gray.Cols - 50*/; i++)
            {
                curgrayList.Add(this.FanghanOffsetForNewKaiKouOffset0_areaMin(gray, i, rowStart, rowEnd));
                if (curgrayList[i-colStart] < minGray)
                {
                    minColIndex = i;
                    minGray = curgrayList[i - colStart];
                }
            }
            for (int i = colStart/*6*//*1*/; i < (gray.Cols + colStart) / 2 /*gray.Cols - 50*/; i++)
            {
                if (i > colStart + 10 && i < (gray.Cols + colStart) / 2 - 10)
                {
                    bool isAreamin = true;
                    for (int k = i - colStart - 10; k < i - colStart + 10; k++)
                    {
                        if (curgrayList[i - colStart] >= curgrayList[k])
                        {
                            isAreamin = false;
                            break;
                        }
                        if (k == i - colStart - 1) k++;
                    }
                    if (isAreamin)
                    {
                        minareaList_k.Add(i);
                        minareaList_v.Add(curgrayList[i - colStart]);
                    }
                }

            }
            //Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
            ////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
            //下面为计算极小值，从计算极小值中的序列中选取，替换极大值
            //minareaList.Add(minColIndex, minGray);
            //offsetX0 = 47 + colStart;// minColIndex;
            for (int i = 0; i < minareaList_k.Count; i++)
            {
                if (Math.Abs(minGray- minareaList_v[i]) < 120)
                {
                    minColIndex = minareaList_k[i];
                    break;
                }
            }
            offsetX0 = minColIndex;
            //
        }
        //获取当前行附件最暗的总和
        private int FanghanOffsetForNewKaiKouOffset0_areaMin(Mat gray, int colIndex, int rowStart, int rowEnd)
        {
            int areaMin = 0;
            for (int j = rowStart; j < rowEnd; j++)
            {
                int colMin = 255;
                for (int i = colIndex - 5; i < colIndex + 5; i++)
                    if (gray.At<byte>(j, i) < colMin) colMin = gray.At<byte>(j, i);
                areaMin += colMin;
            }
            return areaMin;
        }

        /// <summary>
        /// 找轮廓的最左、最右点
        /// </summary>
        /// <param name="temp"></param>
        /// <param name="mat"></param>
        /// <param name="type">1左 2右</param>
        /// <returns></returns>
        public OpenCvSharp.Point GetLeftOrRightPoint(OpenCvSharp.Point temp, Mat mat, int type)
        {
            Rect rect = new Rect();
            Mat mask = Mat.Zeros(mat.Rows + 2, mat.Cols + 2, MatType.CV_8UC1);
            Cv2.FloodFill(mat, mask, temp, new Scalar(255), out rect, null, null, FloodFillFlags.Link8);
            mask = mask * 255;
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\mask.png", mask);
            List<OpenCvSharp.Point> points = new List<OpenCvSharp.Point>();
            if (type == 2)
            {
                for (int h = 1; h < temp.Y - 15/*mask.Height - 1*/; h++)
                {
                    for (int w = temp.X; w < temp.X + 10/*0*/; w++)
                    {
                        byte v = mask.At<byte>(h, w);
                        if (v == 255)
                        {
                            points.Add(new OpenCvSharp.Point(w, h));
                        }
                    }
                }
            }
            else
            {
                for (int h = temp.Y - 45; h < temp.Y - 15/*mask.Height - 1*/; h++)
                {
                    for (int w = temp.X - 200; w < temp.X + 200; w++)
                    {
                        byte v = mask.At<byte>(h, w);
                        if (v == 255)
                        {
                            mask.Set<byte>(h, w, 127);
                            points.Add(new OpenCvSharp.Point(w, h));
                        }
                    }
                }
            }

            if (points.Count == 0) return temp;//1（16）.JPG:1315
            if (points.Count > 5000)//、0（71）.JPG     //0（7）.JPG、0（16）.JPG、0（71）.JPG、1（10）.JPG、3（24）.JPG、3983TT.JPG、5626.JPG
            {//6207.JPG、//6257.JPG
                ////Cv2.DrawContours(mask, new List<OpenCvSharp.Point[]>() { points.ToArray() }, 0, new Scalar(127));
                //////Cv2.DrawContours(mask, new OpenCvSharp.Point[][] { points.ToArray() }, 0, new Scalar(127), 2. );
                //Cv2.ImWrite(@"C:\Users\54434\Desktop\mask.png", mask);
            }
            else if (points.Count > 3000)//0（7）.JPG、0（16）.JPG、0（71）.JPG、1（10）.JPG、3（24）.JPG、3983TT.JPG、5626.JPG
            {//6207.JPG、//6257.JPG
                ////Cv2.DrawContours(mask, new List<OpenCvSharp.Point[]>() { points.ToArray() }, 0, new Scalar(127));
                //////Cv2.DrawContours(mask, new OpenCvSharp.Point[][] { points.ToArray() }, 0, new Scalar(127), 2. );
                //Cv2.ImWrite(@"C:\Users\54434\Desktop\mask.png", mask);
            }
            else if (points.Count > 500 && points.Count < 1000)//0（23）.JPG、999（2）.JPG、3986.JPG[581<-isokay]
            {//9999（5）.JPG
                ////Cv2.DrawContours(mask, new List<OpenCvSharp.Point[]>() { points.ToArray() }, 0, new Scalar(127));
                //////Cv2.DrawContours(mask, new OpenCvSharp.Point[][] { points.ToArray() }, 0, new Scalar(127), 2. );
                //Cv2.ImWrite(@"C:\Users\54434\Desktop\mask.png", mask);
            }
            else
            {//0（3）.JPG
                //Cv2.ImWrite(@"C:\Users\54434\Desktop\mask.png", mask);

                List<OpenCvSharp.Point> points2 = new List<OpenCvSharp.Point>();
                if (type == 2)
                {
                    for (int h = 1; h < temp.Y - 15/*mask.Height - 1*/; h++)
                    {
                        for (int w = temp.X; w < temp.X + 10/*0*/; w++)
                        {
                            byte v = mask.At<byte>(h, w);
                            if (v > 100)
                            {
                                points2.Add(new OpenCvSharp.Point(w, h));
                            }
                        }
                    }
                }
                else
                {//0（3）.JPG
                    for (int h = temp.Y - 45; h < temp.Y - 15/*mask.Height - 1*/; h++)
                    {
                        for (int w = temp.X - 200; w < temp.X + 200; w++)
                        {
                            byte v = mask.At<byte>(h, w);
                            Scalar sum = mask[h - 35, h + 35, w - 1, w + 1].Sum();
                            if (v > 100 && (int)sum>(10000*v/ 255))
                            {
                                points2.Add(new OpenCvSharp.Point(w, h));
                            }
                        }
                    }
                }
                Console.WriteLine("type : " + type);
                if (points2.Count > points.Count/2)
                {//0（3）.JPG
                    points.Clear();
                    points.AddRange(points2);
                }
            }

            if (type == 1)
            {
                return points.Find(a => a.X == points.Min(b => b.X));
            }
            else
            {
                return points.Find(a => a.X == points.Max(b => b.X));
            }
        }

        /// <summary>
        /// 防焊 有开口 计算开口长度
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="fanghankaikou"></param>
        /// <param name="i"></param>
        public void FanhanKaikouForYouKaiKou(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, int fanghanhouduX, int tonghouX, int[] offsetX, out int[] fanghankaikou, int i = 0)
        {
            int tempj = 0;
            //二值化
            float threshold = BinaryTools.CalcSuitableValue(gray);
            Mat threshEdge = gray.Threshold((threshold < 35 ? 65 : threshold) - 10 + (i * 3), 255, ThresholdTypes.BinaryInv);
            //去碎屑
            threshEdge = ~BinaryTools.DebrisRemoval_New(threshEdge.CvtColor(ColorConversionCodes.GRAY2BGRA), 3000).CvtColor(ColorConversionCodes.BGRA2GRAY);
            fanghankaikou = new int[2];
            int tempy = b[3] + (b[2] - offsetX[0]) + 100;// 100;
            if (tempy > threshEdge.Cols - 1) tempy = threshEdge.Cols - 1;
            for (int j = b[3]; j < tempy; j++)
            {
                if (threshEdge.At<byte>(tonghouY[0] - 5, j) == 0/* && threshEdge.At<byte>(tonghouY[0], tonghouX)==0 && threshEdge.At<byte>(fanghanhouY[0], fanghanhouduX) == 0*/)
                {
                    Mat temp = ~threshEdge;
                    if (Cv2.FloodFill(temp, new Point(j, tonghouY[0] - 5), new Scalar(255)) > 3000 && Math.Abs(b[3] + (b[2] - offsetX[0]) - j) < 50)
                    {
                        tempj = j;
                        //Cv2.ImWrite(@"C:\Users\54434\Desktop\threshEdge.png", threshEdge);
                        fanghankaikou[1] = this.GetLeftOrRightPoint(new Point(j, tonghouY[0] - 5), threshEdge, 1).X - 3;
                        break;
                    }
                }
                else if(threshEdge.At<byte>(tonghouY[0] - 15, j) == 0)
                {
                    Mat temp = ~threshEdge;
                    if (Cv2.FloodFill(temp, new Point(j, tonghouY[0] - 15), new Scalar(255)) > 3000 && Math.Abs(b[3] + (b[2] - offsetX[0]) - j) < 70)
                    {
                        tempj = j;
                        fanghankaikou[1] = this.GetLeftOrRightPoint(new Point(j, tonghouY[0] - 15), threshEdge, 1).X - 3;
                        break;
                    }
                }
                else if (threshEdge.At<byte>(tonghouY[0] - 25, j) == 0)
                {
                    Mat temp = ~threshEdge;
                    if (Cv2.FloodFill(temp, new Point(j, tonghouY[0] - 25), new Scalar(255)) > 3000 && Math.Abs(b[3] + (b[2] - offsetX[0]) - j) < 95)
                    {
                        tempj = j;
                        fanghankaikou[1] = this.GetLeftOrRightPoint(new Point(j, tonghouY[0] - 25), threshEdge, 1).X - 3;
                        break;
                    }
                }
            }

            if (i >= 10)
            {//0（48）.JPG、1（10）.JPG、1（73）.JPG[需要镜像处理]、3（3）.JPG、999（4）.JPG、999（5）.JPG、5669.JPG、6028.JPG【需要调试处理,画视场后不走这里了】
                //6111.JPG、9999（7）.JPG【旋转后除了offset右端点其余完美结果】
                //fanghankaikou[1] = b[3] + (b[2]- offsetX[0]);
                if (fanghankaikou[1] > gray.Width) fanghankaikou[1] = b[3] - (b[2] - offsetX[0]);
            }
            else
            {
                if (fanghankaikou[1] == 0/* || (fanghankaikou[1] > 0 && threshEdge.At<byte>(fanghanhouY[1], fanghankaikou[1]) > 0)*/)
                {
                    FanhanKaikouForYouKaiKou(gray, tonghouY, b, fanghanhouY, fanghanhouduX, tonghouX, offsetX, out fanghankaikou, ++i);
                }
                else
                {
                    if(/*Math.Abs(b[3] + (b[2] - offsetX[0]) - fanghankaikou[1]) > 50 || */fanghankaikou[1]> gray.Width)
                    {
                        fanghankaikou[1] = tempj;
                    }
                }
            }
        }

        /// <summary>
        /// 防焊 有开口 LPI
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="LPIHouduY"></param>
        /// <param name="a"></param>
        public void FanghanLPIForYouKaiKou(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] LPIHouduY, int a = 0)
        {
            int LPIHouduX = b[1] + 100;
            LPIHouduY = new int[2];
            Mat result1 = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5), 255, ThresholdTypes.Binary);
            LPIHouduY[0] = tonghouY[1];

            for (int i = LPIHouduY[0] - 120 - Math.Abs(tonghouY[1] - tonghouY[0]); i < LPIHouduY[0] - 50; i++)
            {
                if (result1.At<byte>(i, LPIHouduX) == 0)
                {
                    Mat temp = ~result1;
                    if (Cv2.FloodFill(temp, new Point(LPIHouduX, i), new Scalar(255)) > 3500)
                    {
                        LPIHouduY[1] = i;
                        break;
                    }
                }
            }

            if (LPIHouduY[1] == 0)
            {
                FanghanLPIForYouKaiKou(gray, tonghouY, b, fanghanhouY, out LPIHouduY, ++a);
            }
        }

        /// <summary>
        /// 防焊 有开口 Undercut
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="offsetX"></param>
        /// <param name="LPIHouY"></param>
        /// <param name="undercutX"></param>
        /// <param name="i"></param>
        public void FanghanUndercutForYouKaiKou(Mat gray, int[] tonghouY, int[] b, int[] offsetX, int[] LPIHouY, out int undercutX, int i = 0)
        {
            int tempj = -1;
            undercutX = 0;
            Mat filter = new Mat();
            PointEnhancement(gray, out filter);
            Mat newGray = new Mat();
            Cv2.GaussianBlur(filter, newGray, new Size(15, 15), 5, 5);

            Mat threshEdge = newGray.Threshold(BinaryTools.CalcSuitableValueForUnderCut(gray) - 15 + (i * 3), 255, ThresholdTypes.BinaryInv);
            Mat result = threshEdge.Canny(0, 255);

            //Cv2.ImWrite(@"C:\Users\zyh\Desktop\a.jpg", result*255);
            int tempRange = (offsetX[0] - 300) <= 0 ? 1 : offsetX[0] - 300;
            //想左找
            for (int j = offsetX[0] + 10; j > tempRange; j--)
            {
                byte v = result.Get<byte>((tonghouY[1] + tonghouY[0]) / 2, j);
                if (v > 0)
                {
                    tempj = j;
                    //if (Cv2.FloodFill(result, new Point(j, (tonghouY[1] + tonghouY[0]) / 2), new Scalar(255)) > 100)
                    {
                        undercutX = Tools.GetLeftPoint(new Point(j, (tonghouY[1] + tonghouY[0]) / 2), result).X;
                        break;
                    }
                }
            }

            if (i > 15)
            {
                undercutX = (tempj == -1) ? offsetX[0] - 25 : tempj;
                //undercutX = offsetX[0] - 25;
            }
            else
            {
                if (undercutX == 0 /*|| (undercutX > 0 && offsetX[0] - undercutX > 100)*/)
                {
                    if(undercutX > 0 && Math.Abs(offsetX[0]-tempj) < 50)
                    {
                        undercutX = tempj;
                    }
                    else
                    {
                        FanghanUndercutForYouKaiKou(gray, tonghouY, b, offsetX, LPIHouY, out undercutX, ++i);
                    }
                }
                else
                {
                    undercutX = (undercutX + tempj) / 2 - 5;
                    if(offsetX[0] - undercutX<10) undercutX = (tempj == -1) ? offsetX[0] - 25 : tempj;
                    if (undercutX > offsetX[0]) undercutX = offsetX[0] - 25;
                }
            }
        }

        #endregion

        #region 双面铜


        /// <summary>
        /// 防焊 有开口 offset
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="offsetX"></param>
        /// <param name="i"></param>
        public void FanghanOffsetForShuangmianTong_Acc(Mat gray0, int[] tonghouY, int[] b, int[] fanghanhouY, int offsetY, int offsetX0_0, out int offsetX0)
        {
            int offsetY1 = Math.Max(0, fanghanhouY[1] - 50);
            int offsetY2 = Math.Min(gray0.Rows - 1, tonghouY[1] + 50);
            int offsetLeft = b[1] + 5;
            Mat gray = gray0[offsetY1, offsetY2, offsetLeft, b[2] - 5];
            int colStart = offsetX0_0 - 10 - offsetLeft;
            int colEnd = offsetX0_0 + 20/*10*/ - offsetLeft;

            int minGray = 300 * 255; int minColIndex = 0; int rowStart = offsetY - 10 - offsetY1; int rowEnd = offsetY + 10 - offsetY1;
            List<int> curgrayList = new List<int>();
            List<int> minareaList_k = new List<int>();
            List<int> minareaList_v = new List<int>();
            for (int i = colStart; i < colEnd; i++)
            {
                curgrayList.Add(this.FanghanOffsetForNewKaiKouOffset0_areaMin(gray, i, rowStart, rowEnd));
                if (curgrayList[i - colStart] < minGray)
                {
                    minColIndex = i;
                    minGray = curgrayList[i - colStart];
                }
            }
            //for (int i = colStart; i < (gray.Cols + colStart) / 2; i++)
            //{
            //    if (i > colStart + 10 && i < (gray.Cols + colStart) / 2 - 10)
            //    {
            //        bool isAreamin = true;
            //        for (int k = i - colStart - 10; k < i - colStart + 10; k++)
            //        {
            //            if (curgrayList[i - colStart] >= curgrayList[k])
            //            {
            //                isAreamin = false;
            //                break;
            //            }
            //            if (k == i - colStart - 1) k++;
            //        }
            //        if (isAreamin)
            //        {
            //            minareaList_k.Add(i);
            //            minareaList_v.Add(curgrayList[i - colStart]);
            //        }
            //    }

            //}
            ////Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
            //////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
            ////下面为计算极小值，从计算极小值中的序列中选取，替换极大值
            ////minareaList.Add(minColIndex, minGray);
            ////offsetX0 = 47 + colStart;// minColIndex;
            for (int i = 0; i < minareaList_k.Count; i++)
            {
                if (Math.Abs(minGray - minareaList_v[i]) < 120)
                {
                    minColIndex = minareaList_k[i];
                    break;
                }
            }
            offsetX0 = minColIndex;

            offsetX0 = offsetX0 + offsetLeft;

        }

        /// <summary>
        /// 防焊 有开口 offset
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="offsetX"></param>
        /// <param name="i"></param>
        public void FanghanOffsetForShuangmianTong(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, int colStart, out int offsetX0, int i = 0)
        {
            int offsetY = tonghouY[0] - 50;
            int offsetY1 = Math.Max(0, fanghanhouY[1]/*offsetY*/ - 50);
            int offsetY2 = Math.Min(gray.Rows - 1, tonghouY[1] + 50);
            int offsetLeft = b[1] + 5;
            if (offsetLeft >= b[2] - 5) offsetLeft = b[2] - 5 - 1;
            Mat grayRect = gray[offsetY1, offsetY2, offsetLeft, b[2] - 5];
            this.FanghanOffsetForNewShuangmiantongOffset0(grayRect, colStart, out offsetX0);
            offsetX0 = offsetX0 + offsetLeft;

            ////二值化
            //Mat threshEdge = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (i * 5), 255, ThresholdTypes.BinaryInv);
            ////去碎屑
            //threshEdge = ~BinaryTools.DebrisRemoval_New(threshEdge.CvtColor(ColorConversionCodes.GRAY2BGRA), 250).CvtColor(ColorConversionCodes.BGRA2GRAY);
            //for (int j = b[2] - 55; j > 0; j--)
            //{
            //    if (threshEdge.At<byte>(offsetY + 45, j) == 0)
            //    {
            //        Mat temp = ~threshEdge;
            //        if (Cv2.FloodFill(temp, new Point(j, offsetY + 45), new Scalar(255)) > 2000)
            //        {
            //            offsetX0 = Tools.GetLeftOrRightPoint(new Point(j, offsetY + 45), threshEdge, 2).X;
            //            break;
            //        }
            //    }
            //}
            //if (i  <20 && (offsetX0 <= 0 || Math.Abs(b[2]/*offsetX_1*/ - offsetX0) > 800))
            //    FanghanOffsetForYouKaiKou(gray, tonghouY, b, fanghanhouY, out offsetX0, ++i);
        }
        public void FanghanOffsetForNewShuangmiantongOffset0(Mat gray, int colStart, out int offsetX0)
        {//计算数值的地方
         ////Console.WriteLine("fanghanhouduY1_0:" + fanghanhouduY1);
         //   offsetX0 = -1;
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray.png", gray);
            int minGray = 300 * 255; int minColIndex = 0; int rowStart = 50 + 30; int rowEnd = 130 + 20/*gray.Rows - 50*/;// int curGray;
            List<int> curgrayList = new List<int>();
            List<int> minareaList_k = new List<int>();
            List<int> minareaList_v = new List<int>();
            for (int i = colStart/*6*//*1*/; i < (gray.Cols + colStart) / 2 + 60/* + 40*/ + 20/*10*//*0 debug ER（14）.JPG！！！！*/ /*gray.Cols - 50*/; i++)
            {
                curgrayList.Add(this.FanghanOffsetForNewKaiKouOffset0_areaMin(gray, i, rowStart, rowEnd));
                if (curgrayList[i - colStart] < minGray)
                {
                    minColIndex = i;
                    minGray = curgrayList[i - colStart];
                }
            }
            for (int i = colStart/*6*//*1*/; i < (gray.Cols + colStart) / 2 + 60/* + 40*/ /*gray.Cols - 50*/; i++)
            {
                if (i > colStart + 10 && i < (gray.Cols + colStart) / 2 + 60/* + 40*/ + 10/* - 10 debug ER（14）.JPG！！！！*/)
                {
                    bool isAreamin = true;
                    for (int k = i - colStart - 10; k < i - colStart + 10; k++)
                    {
                        if (curgrayList[i - colStart] >= curgrayList[k])
                        {
                            isAreamin = false;
                            break;
                        }
                        if (k == i - colStart - 1) k++;
                    }
                    if (isAreamin)
                    {
                        minareaList_k.Add(i);
                        minareaList_v.Add(curgrayList[i - colStart]);
                    }
                }

            }
            //Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
            ////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
            //下面为计算极小值，从计算极小值中的序列中选取，替换极大值
            //minareaList.Add(minColIndex, minGray);
            //offsetX0 = 47 + colStart;// minColIndex;
            //if (minColIndex - minareaList_k[minareaList_k.Count - 1] != 0 && minareaList_k.Count < 4)//ER（14）.JPG！！！！
            if (minareaList_k.Count <= 7)
                for (int i = 0; i < minareaList_k.Count; i++)
            {
                if (Math.Abs(minGray - minareaList_v[i]) < 400/*1100*//*400*//*120*/ && minareaList_k[i] > 240/* ER（90）.JPG 250*//* ER（17）.JPG！！！！240*/
                        && (minColIndex > (gray.Cols + colStart) / 2/* + 40*/ + 10 || minColIndex < (gray.Cols + colStart) / 2 + 60 /* + 40*/ - 40))
                {
                    minColIndex = minareaList_k[i];
                    break;
                }
                }
            //纠正191情况
            else if (minareaList_k.Count == 9 && Math.Abs(minGray - minareaList_v[minareaList_k.Count - 2]) < 400
                && minGray - minareaList_v[minareaList_k.Count - 2] != 0)
            {
                minColIndex = minareaList_k[minareaList_k.Count - 2];
            }
            //纠正139情况
            else if (minareaList_k.Count == 8 && Math.Abs(minGray - minareaList_v[minareaList_k.Count - 3]) < 400
                && minGray - minareaList_v[minareaList_k.Count - 3] != 0)
            {
                minColIndex = minareaList_k[minareaList_k.Count - 3];
            }
            if (minColIndex - minareaList_k[minareaList_k.Count - 1] > 0
                && minColIndex - minareaList_k[minareaList_k.Count - 1] < 60
                && Math.Abs(minGray - minareaList_v[minareaList_k.Count - 1]) < 1000)
                minColIndex = minareaList_k[minareaList_k.Count - 1];
            else if (minColIndex - minareaList_k[minareaList_k.Count - 1] < 0 && Math.Abs(minGray - minareaList_v[minareaList_k.Count - 1]) < 1000
                && minareaList_k.Count < 6/*6*//*7*/ /* ER（163）.JPG ER（133）.JPG ER（42）.JPG*/
                  && minColIndex - minareaList_k[minareaList_k.Count - 1] < -40 && minColIndex - minareaList_k[minareaList_k.Count - 1] > -45)
                minColIndex = minareaList_k[minareaList_k.Count - 1];//ER（150）.JPG
            offsetX0 = minColIndex;
            //
        }

        /// <summary>
        /// 防焊 有开口 LPI
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="LPIHouduY"></param>
        /// <param name="a"></param>
        public void FanghanLPIForShuangmianTong(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] LPIHouduY, int a = 0)
        {
            int LPIHouduX = b[1] + 100;
            LPIHouduY = new int[2];
            //Mat result1 = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5), 255, ThresholdTypes.Binary);
            LPIHouduY[0] = tonghouY[1];
            if (a > 255)
            {
                return;
            }
            Mat result1 = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5), 255, ThresholdTypes.Binary);

            for (int i = Math.Max(0, LPIHouduY[0] - 120 - Math.Abs(tonghouY[1] - tonghouY[0])); i < LPIHouduY[0] - 50; i++)
            {
                if (result1.At<byte>(i, LPIHouduX) == 0)
                {
                    Mat temp = ~result1;
                    if (Cv2.FloodFill(temp, new Point(LPIHouduX, i), new Scalar(255)) > 3500)
                    {
                        LPIHouduY[1] = i;
                        break;
                    }
                }
            }

            if (LPIHouduY[1] == 0)
            {
                FanghanLPIForShuangmianTong(gray, tonghouY, b, fanghanhouY, out LPIHouduY, ++a);
            }
        }

        /// <summary>
        /// 防焊 有开口 厚度
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        /// <param name="tonghouY"></param>
        /// <param name="fanghanhouduY"></param>
        /// <param name="a"></param>
        public void FanghanhouduForShuangmianTonghou_2(Mat gray, int[] y, int fanghanhouduX, int[] tonghouY, out int fanghanhouduY1, out int minGray, bool isLeft)
        {
            int fanghanhouduY_0 = tonghouY[0];
            int fanghanX1 = Math.Max(0, fanghanhouduX - 150);
            int fanghanX2 = Math.Min(gray.Cols - 1, fanghanhouduX + 150);
            int fanghanTop = fanghanhouduY_0 - 150/*100*/;
            int marginTop = 150;
            if (fanghanTop < 0)
            {
                fanghanTop = 0;
                marginTop = fanghanhouduY_0 - 1;
            }
            Mat grayRect = gray[fanghanTop, fanghanhouduY_0 - 50, fanghanX1, fanghanX2];
            FanghanhouduForYouKaiKou(grayRect/*gray*/, y, marginTop/*150*//*fanghanhouduX*/, tonghouY, out fanghanhouduY1, out minGray);
            int fanghanhouduY1__2 = fanghanhouduY1;
            int minGray__2 = minGray;
            fanghanX1 += 140;// 145;
            fanghanX2 -= 140;// 145;
            grayRect = gray[fanghanTop, fanghanhouduY_0 - 20/*50*/, fanghanX1, fanghanX2];
            int fanghanhouduY1__2_bottom;
            FanghanhouduForYouKaiKou_ACC(grayRect, y, marginTop, fanghanhouduY1 - (isLeft ? 8/*5*/ : 1), out fanghanhouduY1__2, out fanghanhouduY1__2_bottom, out minGray__2);

            if (Math.Abs(fanghanhouduY1 - fanghanhouduY1__2) < 16/*11*//*<-10*//*20*//*10*/
                || (!isLeft && Math.Abs(fanghanhouduY1 - fanghanhouduY1__2) < 25/*20*/))
                fanghanhouduY1 = fanghanhouduY1__2/*fanghanhouduY1__2_bottom*//*fanghanhouduY1__2*/ + fanghanTop;// +5;
            //else
            //{
            //    fanghanX1 -= 69;
            //    fanghanX2 += 69;
            //    grayRect = gray[fanghanTop, fanghanhouduY_0 - 50, fanghanX1, fanghanX2];
            //    FanghanhouduForMeiKaiKou(grayRect, y, marginTop, tonghouY, out fanghanhouduY1__2, out minGray__2);
            //}
            //if (Math.Abs(fanghanhouduY1 - fanghanhouduY1__2) < 10)
            //    fanghanhouduY1 = fanghanhouduY1__2 + fanghanTop;
            else
                fanghanhouduY1 = fanghanhouduY1 + fanghanTop;
        }

        /// <summary>
        /// 防焊 有开口 厚度
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        /// <param name="tonghouY"></param>
        /// <param name="fanghanhouduY"></param>
        /// <param name="a"></param>
        private void FanghanhouduForShuangmianTonghou(Mat gray, int[] y, int fanghanhouduX, int[] tonghouY, out int fanghanhouduY1, out int minGray, int a = 0)
        {
            /*int fanghanhouduX = 150; */
            fanghanhouduY1 = -1;
            Mat thresh = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5), 255, ThresholdTypes.Binary);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", thresh);
            for (int i = 0; i < 100; i++)
            {
                if (thresh.At<byte>(i, fanghanhouduX) == 0 && Cv2.FloodFill(thresh, new Point(fanghanhouduX, i), new Scalar(255)) > 300)
                {
                    fanghanhouduY1 = i;
                    break;
                }
            }
            minGray = 300 * 255;
            if (fanghanhouduY1 == -1)
                FanghanhouduForShuangmianTonghou(gray, y, fanghanhouduX, tonghouY, out fanghanhouduY1, out minGray, ++a);
            else
            {//计算数值的地方
             //Console.WriteLine("fanghanhouduY1_0:" + fanghanhouduY1);
                /*int minGray = 300*255; */
                int minRowIndex = 0; int colEnd = thresh.Cols - 1; int curGray;
                for (int i = 6/*1*/; i < 95; i++)
                {
                    curGray = this.FanghanhouduForAreaMin(gray, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                    if (curGray < minGray)
                    {
                        minRowIndex = i;
                        minGray = curGray;
                    }
                }
                //Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
                ////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
                fanghanhouduY1 = minRowIndex;
            }
        }

        /// <summary>
        /// 防焊 双面铜 铜厚
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        public void FanhanShuangcengTonghou_1(Mat gray, out int[] tonghouY, out int[] y, out int[] b, int autoResValue = -1)
        {
            y = new int[2];
            b = new int[4];
            int[] bAdd = new int[6];
            tonghouY = new int[2];
            Mat contour;
            //contour = gray.Threshold(180, 255, ThresholdTypes.Binary);
            if (autoResValue > 0)
            {
                contour = gray.Threshold(autoResValue, 255, ThresholdTypes.Binary);
            }
            else
                contour = gray.Threshold(0, 255, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(15, 15));
            Mat close = new Mat();
            Cv2.MorphologyEx(contour, close, MorphTypes.Close, seClose);
            Mat nomin = new Mat();
            GetArea(close, out nomin, 500, true);
            Mat result = nomin.Clone();
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\result.png", result * 127);
            #region//计算边界
            Scalar sum = new Scalar(0);
            for (int i = 0; i < result.Rows; i++)
            {
                sum = result[i, i + 1, /*0*/result.Cols / 2, result.Cols].Sum();
                if ((int)sum > 200)
                {
                    y[0] = i - 20;
                    break;
                }
            }
            for (int i = y[0] + 50; i < result.Rows; i++)
            {
                sum = result[i, i + 1, /*0*/result.Cols / 2, result.Cols].Sum();
                if ((int)sum == 0)
                {
                    y[1] = i;
                    break;
                }
            }
            Mat imageClone = result * 127;
            Cv2.Line(imageClone, 0, y[1], imageClone.Cols - 1, y[1], new Scalar(255));
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\result.png", imageClone);

            for (int j = 0; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum > (/*y[1] - y[0] - */20))
                {
                    b[0] = j; bAdd[0] = j;
                    break;
                }
            }
            //这里可以考虑再次纠错，使用联通域，找到这个联通块的最右侧的点，而不是直接+200
            //但是也要考虑左右的铜，因为底部颜色亮，而连接在一起的情况
            //或者考虑sum==0和另一个条件比较，再次校验
            for (int j = b[0] + 200; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum == 0 || ((int)sum > 0 && ((y[1]-y[0]) - (int)sum)>50))
                //if ((int)sum == 0)
                {
                    b[1] = j; bAdd[1] = j;
                    break;
                }
            }
            for (int j = b[1] + 50; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum > 50)
                //if ((int)sum > (y[1] - y[0] - 20))
                {
                    b[2] = j; bAdd[2] = j;
                    break;
                }
            }
            if (b[2] - b[1] < 300)
            {
                for (int j = b[2] + 50; j < result.Cols; j++)
                {
                    sum = result[y[0], y[1], j, j + 1].Sum();
                    if ((int)sum == 0)
                    {
                        b[1] = j;
                        bAdd[1] = j;
                        break;
                    }
                }
                for (int j = b[1] + 10; j < result.Cols; j++)
                {
                    sum = result[y[0], y[1], j, j + 1].Sum();
                    if ((int)sum > 20)
                    {
                        b[2] = j;
                        bAdd[2] = j;
                        break;
                    }
                }
            }
            for (int j = b[2] + 50; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum == 0)
                {
                    b[3] = j;
                    bAdd[3] = j;
                    break;
                }
            }
            if (b[3] == 0)
                b[3] = contour.Cols - 1;
            if (bAdd[3] == 0)
                bAdd[3] = contour.Cols - 1;


            for (int j = bAdd[3] + 10; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum > 0)
                {
                    bAdd[4] = j;
                    break;
                }
            }
            if (bAdd[4] == 0)
                bAdd[4] = contour.Cols - 1;
            for (int j = bAdd[4] + 50; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum == 0)
                {
                    bAdd[5] = j;
                    break;
                }
            }
            if (bAdd[5] == 0)
                bAdd[5] = contour.Cols - 1;


            //    for (int j = result.Cols - 1; j > b[2]; j--)
            //    {
            //        sum = result[y[0], y[1], j - 1, j].Sum();
            //        if ((int)sum > 0)
            //        {
            //            b[3] = j;
            //            break;
            //        }
            //    }
            //    if (b[3] == 0)
            //        b[3] = contour.Cols - 1;
            //    //bAdd[5] = b[3];
            if (b[3] != bAdd[5] && bAdd[5] != contour.Cols - 1)//b[3] != bAdd[3] && b[3] - bAdd[2] > bAdd[3] - b[0] && (b[0] < 20 && b[1] < 60 && (b[1] < 280 && b[0] < 100 || b[3] == contour.Cols - 1))/*防止过拟合*/)//测量区域在右边
            {
                b[3] = bAdd[5];//
                b[2] = bAdd[4];
                b[1] = bAdd[3];
                b[0] = bAdd[2];
            }
            #endregion
            //计算铜厚
            Mat filter = new Mat();
            Cv2.GaussianBlur(gray, filter, new Size(15, 15), 5, 5);
            Mat edge = new Mat();
            Sobel(filter, out edge);
            Mat threshEdge = edge.Threshold(10, 255, ThresholdTypes.Binary);

            Mat and = new Mat();
            Cv2.BitwiseAnd(contour, threshEdge, and);
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(9, 1));
            Mat open = new Mat();
            Cv2.MorphologyEx(and, open, MorphTypes.Open, seOpen);
            Cv2.Rectangle(open, new Rect(0, y[1], open.Cols, open.Rows - y[1]), new Scalar(0), -1);
            int tonghouX = b[1] - 150;

            #region//计算边界 在tonghouX附近纠正y轴倾斜的距离
            sum = new Scalar(0);
            for (int i = 0; i < result.Rows; i++)
            {
                sum = result[i, i + 1, tonghouX - 10, tonghouX + 10/*result.Cols / 2, result.Cols*/].Sum();
                if ((int)sum > 10/*200*/)
                {
                    y[0] = i - 20;
                    break;
                }
            }
            for (int i = y[0] + 50; i < result.Rows; i++)
            {
                sum = result[i, i + 1, tonghouX - 10, tonghouX + 10/*result.Cols / 2, result.Cols*/].Sum();
                if ((int)sum == 0)
                {
                    y[1] = i;
                    break;
                }
            }
            #endregion



            Mat result2 = open / 255;
            int start = 0;
            for (int i = y[0]; i < y[1]; i++)
            {
                if (contour.Get<byte>(i, tonghouX) > 0)
                {
                    start = i;
                    break;
                }
            }
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\result2.png", result2 * 127);
            for (int i = start + 20; i < y[1] - 40/*40*/; i++)
            {
                sum = result2[i, i + 1, tonghouX - 50, tonghouX + 50].Sum();
                if ((int)sum > 80/*80*/)
                {
                    tonghouY[0] = i;
                    break;
                }
            }
            if (tonghouY[0] == 0)
            {
                for (int i = start + 20; i < y[1] - 20; i++)
                {
                    sum = result2[i, i + 1, tonghouX - 50, tonghouX + 50].Sum();
                    if ((int)sum > 50)
                    {
                        tonghouY[0] = i;
                        break;
                    }
                }
            }
            //if (tonghouY[0] == 0)
            //{//ER（114）.JPG
            //    //tonghouY[0] = start;
            //    for (int i = start - 50/* + 20*/; i < y[1] - 0/*20*/; i++)
            //    {
            //        sum = result2[i, i + 1, tonghouX - 50, tonghouX + 50].Sum();
            //        if ((int)sum > 20/*50*/)
            //        {
            //            tonghouY[0] = i;
            //            break;
            //        }
            //    }
            //}
            for (int i = tonghouY[0] + 10; i < y[1] + 20/*0*/; i++)
            {
                if (contour.Get<byte>(i, tonghouX) == 0)
                {
                    tonghouY[1] = i;
                    break;
                }
            }
            int compensate1 = 0;
            tonghouY[0] += compensate1;
        }

        /// <summary>
        /// 防焊 双面铜 铜厚
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        public void FanhanShuangcengTonghou_2(Mat gray, out int[] tonghouY, out int[] y, out int[] b)
        {
            y = new int[2];
            b = new int[4];
            tonghouY = new int[2];
            Mat contour = gray.Threshold(0, 255, ThresholdTypes.Otsu);
            //去掉小颗粒
            contour = BinaryTools.DebrisRemoval_New(contour.CvtColor(ColorConversionCodes.GRAY2BGRA), 1000).CvtColor(ColorConversionCodes.BGRA2GRAY);
            Mat result = contour.Clone();

            /*Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(15, 15));
            Mat close = new Mat();
            Cv2.MorphologyEx(contour, close, MorphTypes.Close, seClose);
            Mat nomin = new Mat();
            GetArea(close, out nomin, 500, true);
            Mat result = nomin.Clone();*/

            #region//计算边界
            Scalar sum = new Scalar(0);
            for (int i = 0; i < result.Rows; i++)
            {
                sum = result[i, i + 1, 0, result.Cols].Sum();
                if ((int)sum > 200)
                {
                    y[0] = i - 20;
                    break;
                }
            }
            for (int i = y[0] + 50; i < result.Rows; i++)
            {
                sum = result[i, i + 1, 0, result.Cols].Sum();
                if ((int)sum == 0)
                {
                    y[1] = i;
                    break;
                }
            }

            for (int j = 0; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum > 20)
                {
                    b[0] = j;
                    break;
                }
            }
            for (int j = b[0] + 200; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum == 0)
                {
                    b[1] = j;
                    break;
                }
            }
            for (int j = b[1] + 10; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum > 20)
                {
                    b[2] = j;
                    break;
                }
            }
            if (b[2] - b[1] < 300)
            {
                for (int j = b[2] + 50; j < result.Cols; j++)
                {
                    sum = result[y[0], y[1], j, j + 1].Sum();
                    if ((int)sum == 0)
                    {
                        b[1] = j;
                        break;
                    }
                }
                for (int j = b[1] + 10; j < result.Cols; j++)
                {
                    sum = result[y[0], y[1], j, j + 1].Sum();
                    if ((int)sum > 20)
                    {
                        b[2] = j;
                        break;
                    }
                }
            }
            for (int j = b[2] + 50; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum == 0)
                {
                    b[3] = j;
                    break;
                }
            }
            if (b[3] == 0)
                b[3] = contour.Cols - 1;
            //LineShow(gray, b[0], y[0], b[1], y[0]);
            //LineShow(gray, b[2], y[1], b[3], y[1]);
            //ImageShow(gray);
            #endregion
            //计算铜厚
            Mat filter = new Mat();
            Cv2.GaussianBlur(gray, filter, new Size(15, 15), 5, 5);
            Mat edge = new Mat();
            //Edge(filter, out edge);
            //Mat threshEdge = edge.Threshold(25, 255, ThresholdTypes.Binary);
            Sobel(filter, out edge);
            Mat threshEdge = edge.Threshold(10, 255, ThresholdTypes.Binary);

            Mat and = new Mat();
            Cv2.BitwiseAnd(contour, threshEdge, and);
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(9, 1));
            Mat open = new Mat();
            Cv2.MorphologyEx(and, open, MorphTypes.Open, seOpen);
            //GetArea(open, out open, 10, true);
            Cv2.Rectangle(open, new Rect(0, y[1], open.Cols, open.Rows - y[1]), new Scalar(0), -1);
            //Mat fanse = 255 - open;
            //Mat noMin = new Mat();
            //GetArea(fanse, out noMin, 1000, true);
            //ImageShow(threshEdge, and, open/*,fanse*255*/);
            int tonghouX = b[1] - 150;
            Mat result2 = open / 255;
            int start = 0;
            for (int i = y[0]; i < y[1]; i++)
            {
                if (contour.Get<byte>(i, tonghouX) > 0)
                {
                    start = i;
                    break;
                }
            }
            for (int i = start + 20; i < y[1] - 40; i++)
            {
                sum = result2[i, i + 1, tonghouX - 50, tonghouX + 50].Sum();
                if ((int)sum > 80)
                {
                    tonghouY[0] = i;
                    break;
                }
            }
            if (tonghouY[0] == 0)
            {
                for (int i = start + 20; i < y[1] - 20; i++)
                {
                    sum = result2[i, i + 1, tonghouX - 50, tonghouX + 50].Sum();
                    if ((int)sum > 50)
                    {
                        tonghouY[0] = i;
                        break;
                    }
                }
            }
            //for (int i = tonghouY[0]+10; i < y[1]; i++)
            //{
            //    sum = result2[i, i + 1, tonghouX - 50, tonghouX + 50].Sum();
            //    if ((int)sum > 50)
            //    {
            //        tonghouY[1] = i;
            //        break;
            //    }
            //}
            for (int i = tonghouY[0] + 10; i < y[1]; i++)
            {
                if (contour.Get<byte>(i, tonghouX) == 0)
                {
                    tonghouY[1] = i;
                    break;
                }
            }
            int compensate1 = 0;
            tonghouY[0] += compensate1;
            //int compensate2 = 10;
            //tonghouY[1] += compensate2;
        }


        /// <summary>
        /// 防焊 双面铜 厚度
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        /// <param name="tonghouY"></param>
        /// <param name="fanghanhouduY"></param>
        public void Fanghanhoudu4(Mat gray, int[] y, int[] b, int[] tonghouY, out int[] fanghanhouduY, int a = 0)
        {
            fanghanhouduY = new int[2];
            int fanghanhouduX = b[1] - 100;
            /*Mat newGray = new Mat();
            Cv2.GaussianBlur(gray, newGray, new Size(15, 15), 5, 5);
            Mat edge = new Mat();
            Sobel(newGray, out edge);
            Mat thresh = edge.Threshold(5, 255, ThresholdTypes.Binary);
            Cv2.Rectangle(thresh, new Rect(0, 0, b[1] - 200, thresh.Rows), new Scalar(0), -1);
            Cv2.Rectangle(thresh, new Rect(0, 0, thresh.Cols, y[0] - 200), new Scalar(0), -1);
            Cv2.Rectangle(thresh, new Rect(0, y[0], thresh.Cols, thresh.Rows - y[0]), new Scalar(0), -1);
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Mat open = new Mat();
            Cv2.MorphologyEx(thresh, open, MorphTypes.Open, seOpen);
            Mat noCircle = new Mat();
            RemoveCircles(open, out noCircle);
            Mat max = new Mat();
            GetMaxArea(noCircle, out max);
            Mat result = max.Clone();
            Scalar sum = new Scalar(0);
            for (int i = tonghouY[0] - 50; i > tonghouY[0] - 200; i--)
            {
                sum = result[i - 1, i, fanghanhouduX - 50, fanghanhouduX + 50].Sum();
                if ((int)sum > 50)
                {
                    fanghanhouduY[0] = i;
                    break;
                }
            }*/
            fanghanhouduY[1] = y[0]+20;
            /*Scalar sum = new Scalar(0);
            Mat thresh = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5), 255, ThresholdTypes.Binary);
            //防焊下层
            Mat thresh2 = thresh / 255;//gray.Threshold(0, 1, ThresholdTypes.Otsu);
            for (int i = fanghanhouduY[0] + 10; i < tonghouY[0]*//*thresh2.Rows*//*; i++)
            {
                sum = thresh2[i, i + 1, fanghanhouduX - 50, fanghanhouduX + 50].Sum();
                if ((int)sum > 50)
                {
                    fanghanhouduY[1] = i;
                    break;
                }
            }*/

            Mat thresh = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 3), 255, ThresholdTypes.Binary);
            for (int i = fanghanhouduY[1] - 50; i > fanghanhouduY[1] - 90; i--)
            {
                if (thresh.At<byte>(i, fanghanhouduX) == 0 && Cv2.FloodFill(thresh, new Point(fanghanhouduX, i), new Scalar(255)) > 1300)
                {
                    fanghanhouduY[0] = i - 4;
                    break;
                }
            }

            if (fanghanhouduY[0] == 0)
            {
                Fanghanhoudu4(gray, y, b, tonghouY, out fanghanhouduY, ++a);
            }

            /*fanghanhouduY = new int[2];
            int fanghanhouduX = b[1] - 100;
            Mat thresh = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5), 255, ThresholdTypes.Binary);

            fanghanhouduY[0] = tonghouY[0];
            for (int i = fanghanhouduY[0] - 100; i < fanghanhouduY[0] - 50; i++)
            {
                if (thresh.At<byte>(i, fanghanhouduX) == 0 && Cv2.FloodFill(thresh, new Point(fanghanhouduX, i), new Scalar(255)) > 300)
                {
                    fanghanhouduY[1] = i;
                    break;
                }
            }

            if (fanghanhouduY[1] == 0)
            {
                Fanghanhoudu4(gray, y, b, tonghouY, out fanghanhouduY, ++a);
            }*/
        }

        /// <summary>
        /// 防焊 双面铜 offset
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="offsetX"></param>
        public void FanghanOffset6(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] offsetX, int i = 0)
        {
            offsetX = new int[2];
            //二值化
            Mat threshEdge = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (i * 5), 255, ThresholdTypes.BinaryInv);
            //去碎屑
            threshEdge = ~BinaryTools.DebrisRemoval_New(threshEdge.CvtColor(ColorConversionCodes.GRAY2BGRA), 250).CvtColor(ColorConversionCodes.BGRA2GRAY);
            for (int j = b[2] - 155; j > 0; j--)
            {
                if (threshEdge.At<byte>(tonghouY[0] - 5, j) == 0)
                {
                    Mat temp = ~threshEdge;
                    if (Cv2.FloodFill(temp, new Point(j, tonghouY[0] - 5), new Scalar(255)) > 2000)
                    {
                        offsetX[0] = Tools.GetLeftOrRightPoint(new Point(j, tonghouY[0] - 5), threshEdge, 2).X;
                        break;
                    }
                }
            }

            offsetX[1] = b[2];

            if (i < 20 && ( offsetX[0] <= 0 || Math.Abs(offsetX[1] - offsetX[0]) > 800))
            {
                FanghanOffset6(gray, tonghouY, b, fanghanhouY, out offsetX, ++i);
            }
        }

        /// <summary>
        /// 防焊 双面铜 LPI厚度
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY">銅厚的上下縱坐標</param>
        /// <param name="b">第一層銅的起始點（橫向），b[0]:銅起始點；b[1]:銅結束點；b[2]:銅再次開始點</param>
        /// <param name="LPIHouduY"></param>
        public void FanghanLPI2(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] LPIHouduY, int a = 0)
        {
            int LPIHouduX = b[1] + 100;
            LPIHouduY = new int[2];
            Mat result1 = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5), 255, ThresholdTypes.Binary);
            LPIHouduY[0] = tonghouY[1];
            if (LPIHouduY[0] <= 120) return;
            for (int i = LPIHouduY[0] - 120 - Math.Abs(tonghouY[1] - tonghouY[0]); i < LPIHouduY[0] - 50; i++)
            {
                if (result1.At<byte>(i, LPIHouduX) == 0)
                {
                    Mat temp = ~result1;
                    if (Cv2.FloodFill(temp, new Point(LPIHouduX, i), new Scalar(255)) > 3500)
                    {
                        LPIHouduY[1] = i;
                        break;
                    }
                }
            }

            if (LPIHouduY[1] == 0)
            {
                FanghanLPI2(gray, tonghouY, b, fanghanhouY, out LPIHouduY, ++a);
            }
        }

        /// <summary>
        /// 防焊 双面铜 Undercut
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="offsetX"></param>
        /// <param name="LPIHouY"></param>
        /// <param name="undercutX"></param>
        /// <param name="i"></param>
        public void FanghanUndercut6_3(Mat gray, int[] tonghouY, int[] b, int[] offsetX, int[] LPIHouY, out int undercutX, int i = 0)
        {
            int tempj = -1;
            undercutX = 0;
            Mat filter = new Mat();
            PointEnhancement(gray, out filter);
            Mat newGray = new Mat();
            Cv2.GaussianBlur(filter, newGray, new Size(15, 15), 5, 5);

            Mat threshEdge = newGray.Threshold(BinaryTools.CalcSuitableValueForUnderCut(gray) - 15 + (i * 3), 255, ThresholdTypes.BinaryInv);
            Mat result = threshEdge.Canny(0, 255);
            int tempRange = (offsetX[0] - 300) <= 0 ? 1 : offsetX[0] - 300;
            //想左找
            for (int j = offsetX[0] + 10; j > tempRange; j--)
            {
                byte v = result.Get<byte>((tonghouY[1] + tonghouY[0]) / 2, j);
                if (v > 0)
                {
                    tempj = j;
                    //if (Cv2.FloodFill(result, new Point(j, (tonghouY[1] + tonghouY[0]) / 2), new Scalar(255)) > 100)
                    {
                        undercutX = Tools.GetLeftPoint(new Point(j, (tonghouY[1] + tonghouY[0]) / 2), result).X;
                        break;
                    }
                }
            }

            if (i > 15)
            {
                undercutX = (tempj == -1) ? offsetX[0] - 25 : tempj;
                //undercutX = offsetX[0] - 25;
            }
            else
            {
                if (undercutX == 0 || (undercutX > 0 && offsetX[0] - undercutX > 100))
                {
                    FanghanUndercut6_3(gray, tonghouY, b, offsetX, LPIHouY, out undercutX, ++i);
                }
                else
                {
                    undercutX = (undercutX + tempj) / 2 - 20;
                }
            }
        }

        #endregion

        #endregion





        /// <summary>
        /// 计算防焊双层铜的铜厚
        /// </summary>
        /// <param name="imageContour">二值圖像</param>
        /// <param name="imageGreen">绿色通道图</param>
        /// <param name="tonghouY">輸出銅厚的上下縱坐標</param>
        /// <param name="y">輸出銅厚的上下縱坐標</param>
        /// <param name="b">b[0]:銅起始點；b[1]:銅結束點；b[2]:銅再次開始點</param>
        public void FanhanShuangcengTonghou(Mat imageContour, Mat imageGreen, out int[] tonghouY, out int[] y, out int[] b)
        {
            y = new int[2];
            b = new int[4];
            tonghouY = new int[2];
            Scalar sum = new Scalar(0);
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Open, se);
            for (int i = 0; i < imageContour.Rows; i++)
            {
                sum = imageContour[i, i + 1, 0, imageContour.Cols].Sum();
                if ((int)sum > 200)
                {
                    y[0] = i - 20;
                    break;
                }
            }
            for (int i = y[0] + 21; i < imageContour.Rows; i++)
            {
                sum = imageContour[i, i + 1, 0, imageContour.Cols].Sum();
                if ((int)sum == 0)
                {
                    y[1] = i;
                    break;
                }
            }
            //左右边界，从右边开始
            for (int j = imageContour.Cols - 1; j > 0; j--)
            {
                sum = imageContour[y[0], y[1], j - 1, j].Sum();
                if ((int)sum > 0)
                {
                    b[3] = j;
                    break;
                }
            }
            for (int j = b[3] - 1; j > 0; j--)
            {
                sum = imageContour[y[0], y[1], j - 1, j].Sum();
                if ((int)sum == 0)
                {
                    b[2] = j;
                    break;
                }
            }
            for (int j = b[2] - 1; j > 0; j--)
            {
                sum = imageContour[y[0], y[1], j - 1, j].Sum();
                if ((int)sum > 0)
                {
                    b[1] = j;
                    break;
                }
            }
            for (int j = b[1] - 1; j > 0; j--)
            {
                sum = imageContour[y[0], y[1], j - 1, j].Sum();
                if ((int)sum == 0)
                {
                    b[0] = j;
                    break;
                }
            }
            //计算外层铜厚
            Mat crop = imageContour[y[0], y[1], b[0], b[2]];

            int tonghouX = b[1] - 200;
            Mat se2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 1));
            Mat dilate = new Mat();
            Cv2.Dilate(crop, dilate, se2);
            Mat result = dilate.Clone();
            GetMaxContour(dilate, out result);
            //ImageShow(result * 255);
            for (int i = 0; i < result.Rows; i++)
            {
                if (result.Get<byte>(i, tonghouX - b[0]) > 0)
                {
                    tonghouY[0] = i + y[0];
                    break;
                }
            }
            for (int i = tonghouY[0] - y[0] + 20; i < result.Rows; i++)
            {
                if (result.Get<byte>(i, tonghouX - b[0]) > 0)
                {
                    tonghouY[1] = i + y[0];
                    break;
                }
            }
            double ordiante = 0;
            InsideLine(imageGreen, tonghouY[0], tonghouY[1], tonghouX - 10, tonghouX + 10, out ordiante);
            tonghouY[0] = (int)ordiante;
        }
        
        /// <summary>
        /// 計算防焊厚度
        /// </summary>
        /// <param name="imageRed">原圖紅色通道圖片</param>
        /// <param name="y">截取第一層銅的上下區域</param>
        /// <param name="b">第一層銅的起始點（橫向），b[0]:銅起始點；b[1]:銅結束點；b[2]:銅再次開始點</param>
        /// <param name="tonghouY">銅厚的上下縱坐標</param>
        /// <param name="fanghanhouduY">防焊厚度的上下縱坐標</param>        
        public void Fanghanhoudu2(Mat imageRed, int[] y, int[] b, int[] tonghouY, out int[] fanghanhouduY)
        {
            int compensate = 5;
            fanghanhouduY = new int[2];
            int fanghanhouduX = b[1] - 100;
            Mat crop = imageRed[tonghouY[0] - 100, tonghouY[0] - 20, /*fanghanhouduX-20, fanghanhouduX+20*/fanghanhouduX - 100, b[1]];
            Mat thresh = new Mat();
            double t = Cv2.Threshold(crop, thresh, 0, 1, ThresholdTypes.Otsu);
            thresh = 1 - crop.Threshold(t - 10, 1, ThresholdTypes.Binary);
            Mat seopen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(10, 3));
            Mat open = new Mat();
            Cv2.MorphologyEx(thresh, open, MorphTypes.Close, seopen);
            Cv2.Rectangle(open, new Rect(0, 0, 1, open.Rows), new Scalar(1), -1);
            Cv2.Rectangle(open, new Rect(0, thresh.Rows - 1, thresh.Cols, 1), new Scalar(1), -1);
            Fill(open, out open, 1);
            Cv2.Rectangle(open, new Rect(0, 0, 1, open.Rows), new Scalar(0), -1);
            Mat result;
            GetMaxArea(open, out result);
            Scalar sum = new Scalar(0);
            for (int i = 0; i < result.Rows; i++)
            {
                sum = result[i, i + 1, 0, result.Cols].Sum();
                if ((int)sum > 5)
                {
                    fanghanhouduY[0] = i + tonghouY[0] - 100 + compensate;
                    break;
                }
            }

            Mat crop3 = imageRed.Threshold(0, 1, ThresholdTypes.Otsu)[y[0], y[1], 0, imageRed.Cols];
            double ordinate2 = 0;
            ExtractLines(crop3, out ordinate2, fanghanhouduX - 5, fanghanhouduX + 5, 1);
            fanghanhouduY[1] = (int)ordinate2 + y[0] + 2;
        }

        public void Fanghanhoudu3(Mat gray, int[] y, int[] b, int[] tonghouY, out int[] fanghanhouduY, int a=0)
        {
            fanghanhouduY = new int[2];
            int fanghanhouduX = b[1] - 100;
            Mat thresh = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a*5), 255, ThresholdTypes.Binary);
            
            fanghanhouduY[0] = tonghouY[0];
            for (int i = fanghanhouduY[0] - 100; i < fanghanhouduY[0] - 50; i++)
            {
                if(thresh.At<byte>(i, fanghanhouduX) == 0 && Cv2.FloodFill(thresh, new Point(fanghanhouduX, i), new Scalar(255)) > 300)
                {
                    fanghanhouduY[1] = i;
                    break;
                }
            }

            if (fanghanhouduY[1] == 0)
            {
                Fanghanhoudu3(gray, y, b, tonghouY, out fanghanhouduY, ++a);
            }
        }

        public void Fanghanhoudu5(Mat gray, int[] y, int[] b, int[] tonghouY, out int[] fanghanhouduY, int a=0)
        {
            fanghanhouduY = new int[2];
            int fanghanhouduX = b[1] - 100;
            Mat thresh = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5), 255, ThresholdTypes.Binary);

            fanghanhouduY[0] = tonghouY[0];
            for (int i = fanghanhouduY[0] - 100; i < fanghanhouduY[0] - 50; i++)
            {
                if (thresh.At<byte>(i, fanghanhouduX) == 0 && Cv2.FloodFill(thresh, new Point(fanghanhouduX, i), new Scalar(255)) > 300)
                {
                    fanghanhouduY[1] = i;
                    break;
                }
            }

            if (fanghanhouduY[1] == 0)
            {
                Fanghanhoudu5(gray, y, b, tonghouY, out fanghanhouduY, ++a);
            }
        }
        
        //public void Fanghanhoudu2(Mat imageRed, int[] y, int[] b, int[] tonghouY, out int[] fanghanhouduY)
        /// <summary>
        /// 計算防焊offset
        /// </summary>
        /// <param name="imageRed">紅色通道圖片</param>
        /// <param name="tonghouY">銅厚縱坐標</param>
        /// <param name="b">第一層銅的起始點（橫向），b[0]:銅起始點；b[1]:銅結束點；b[2]:銅再次開始點</param>
        /// <param name="offsetX">offset橫坐標</param>
        public void FanghanOffset2(Mat imageRed, int[] tonghouY, int[] b, out int[] offsetX)
        {
            offsetX = new int[2];
            Mat crop = imageRed[tonghouY[0] - 100, tonghouY[1] - 20, b[1] + 20, b[2]];
            Mat thresh = new Mat();
            double t = Cv2.Threshold(crop, thresh, 0, 1, ThresholdTypes.Otsu);
            thresh = 1 - crop.Threshold(t - 25, 1, ThresholdTypes.Binary);

            Mat seopen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
            Mat open = new Mat();
            Cv2.MorphologyEx(thresh, open, MorphTypes.Close, seopen);
            Cv2.Rectangle(open, new Rect(0, 0, 1, open.Rows), new Scalar(1), -1);
            Cv2.Rectangle(open, new Rect(0, thresh.Rows - 1, thresh.Cols, 1), new Scalar(1), -1);
            Scalar max = new Scalar(0);
            int maxline = 0;
            for (int i = 0; i < open.Rows - 1; i++)
            {
                if ((int)open[i, i + 1, 0, open.Cols].Sum() > (int)max)
                {
                    max = open[i, i + 1, 0, open.Cols].Sum();
                    maxline = i;
                }
            }
            Cv2.Rectangle(open, new Rect(0, maxline, thresh.Cols, 1), new Scalar(1), -1);
            Fill(open, out open, 1);
            //Cv2.Rectangle(open, new Rect(0, maxline, thresh.Cols, 1), new Scalar(0), -1);
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(1, 3));
            Cv2.Erode(open, open, se);
            Cv2.Rectangle(open, new Rect(0, thresh.Rows - 1, thresh.Cols, 1), new Scalar(0), -1);
            Mat result;
            GetMaxArea(open, out result);
            //ImageShow(thresh * 255, open * 255, result * 255);
            //ImageShow(open * 255, result * 255);
            //Mat noCircle = new Mat();
            //RemoveCirCles(crop, thresh, out noCircle);
            //Mat close = new Mat();
            //Cv2.MorphologyEx(noCircle, close, MorphTypes.Close, seopen);
            ////Cv2.MorphologyEx(close, open, MorphTypes.Open, seopen);
            Scalar sum = new Scalar(0);
            for (int j = 20; j < result.Cols; j++)
            {
                sum = result[0, result.Rows, j, j + 1].Sum();
                if ((int)sum < 2)
                {
                    offsetX[0] = j + b[1] + 20 - 5;
                    break;
                }
            }
            offsetX[1] = b[2];

            //ImageShow(thresh * 255, noCircle * 255, close * 255, open * 255);
            //RemoveCirCles(crop,fill, out noCircle);
            //ImageShow(open*255,fill * 255, noCircle*255);
        }
        public void FanghanOffset3(Mat imageRed, int[] tonghouY, int[] b, out int[] offsetX)
        {
            offsetX = new int[2];
            Mat crop = imageRed[tonghouY[0] - 100, tonghouY[0], b[1], b[2]].Clone();
            Mat sobel = new Mat();
            Sobel(crop, out sobel);
            Mat thresh = sobel.Threshold(0, 255, ThresholdTypes.Otsu);
            Mat fill = new Mat();
            Fill(thresh, out fill, 255);
            Mat deleteArea = new Mat();
            GetArea(fill, out deleteArea, 10, true);
            Cv2.Rectangle(deleteArea, new Rect(0, deleteArea.Rows - 1, deleteArea.Cols, 1), new Scalar(1), -1);
            Cv2.Rectangle(deleteArea, new Rect(0, 0, 1, deleteArea.Rows), new Scalar(1), -1);
            Fill(deleteArea, out deleteArea, 1);
            Cv2.Rectangle(deleteArea, new Rect(0, deleteArea.Rows - 1, deleteArea.Cols, 1), new Scalar(0), -1);
            Cv2.Rectangle(deleteArea, new Rect(0, 0, 1, deleteArea.Rows), new Scalar(0), -1);
            Mat maxArea = new Mat();
            GetMaxArea(deleteArea, out maxArea);
            Scalar sum = new Scalar(0);
            for (int j = maxArea.Cols - 1; j > 0; j--)
            {
                sum = maxArea[0, maxArea.Rows, j - 1, j].Sum();
                if ((int)sum > 0)
                {
                    offsetX[0] = j + b[1];
                    break;
                }
            }
            offsetX[1] = b[2];
            //ImageShow(thresh, fill, deleteArea * 255, maxArea * 255);
        }
        /// <summary>
        /// 提取防焊没开口offset，利用大倍率边缘检测来实现
        /// </summary>
        /// <param name="imageRed"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="offsetX"></param>
        public void FanghanOffset4(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] offsetX)
        {
            offsetX = new int[2];
            //offsetY = 0;
            Mat filter = new Mat();
            PointEnhancement(gray, out filter);
            Mat newGray = new Mat();
            Cv2.GaussianBlur(filter, newGray, new Size(15, 15), 5, 5);

            //PointEnhancement(gray, out gray);
            //Mat crop = gray[tonghouY[0] - 120, tonghouY[0] - 20, LPIHouduX - 10, LPIHouduX + 10];
            Mat edge = new Mat();
            //Sobel(gray, out edge);
            Edge(newGray, out edge);
            Mat threshEdge = new Mat();
            threshEdge = edge.Threshold(35, 255, ThresholdTypes.Binary);

            Cv2.Rectangle(threshEdge, new Rect(0, 0, threshEdge.Cols, fanghanhouY[0]), new Scalar(0), -1);
            Cv2.Rectangle(threshEdge, new Rect(0, 0, b[1], tonghouY[1]), new Scalar(255), -1);
            Cv2.Rectangle(threshEdge, new Rect(0, tonghouY[1], threshEdge.Cols, threshEdge.Rows - tonghouY[1]), new Scalar(0), -1);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(1, 7));
            Mat close = new Mat();
            Cv2.MorphologyEx(threshEdge, close, MorphTypes.Close, seClose);
            Mat noMin = new Mat();
            //GetArea(close, out noMin, 1000, true);
            GetMaxArea(close, out noMin);
            ImageShow(edge, threshEdge, close, noMin * 255);
            Mat result = noMin.Clone();
            Scalar sum = new Scalar(0);
            for (int j = b[2] - 20; j > 0; j--)
            {
                sum = result[fanghanhouY[0], tonghouY[0] - 20, j - 1, j].Sum();
                //if (result.Get<byte>(tonghouY[0] - 50, j) > 0)
                if ((int)sum > 20)
                {
                    offsetX[0] = j;
                    break;
                }
            }
            //for (int i = fanghanhouY[0]; i < tonghouY[0]; i++)
            //{
            //    if (result.Get<byte>(i, offsetX[0]) > 0)
            //    {
            //        offsetY = i;
            //        break;
            //    }
            //}
            offsetX[1] = b[2];
            int compensate = 10;
            offsetX[0] -= compensate;
        }
        /// <summary>
        /// 用于提取防焊有开口的offset，因为图片质量差，所用的参数比没开口低
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="offsetX"></param>
        public void FanghanOffset5(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] offsetX)
        {
            offsetX = new int[2];
            //offsetY = 0;
            Mat filter = new Mat();
            PointEnhancement(gray, out filter);
            Mat newGray = new Mat();
            Cv2.GaussianBlur(filter, newGray, new Size(15, 15), 5, 5);

            //PointEnhancement(gray, out gray);
            //Mat crop = gray[tonghouY[0] - 120, tonghouY[0] - 20, LPIHouduX - 10, LPIHouduX + 10];
            Mat edge = new Mat();
            //Sobel(gray, out edge);
            Edge(newGray, out edge);
            Mat threshEdge = new Mat();
            threshEdge = edge.Threshold(25, 255, ThresholdTypes.Binary);

            Cv2.Rectangle(threshEdge, new Rect(0, tonghouY[1], threshEdge.Cols, threshEdge.Rows - tonghouY[1]), new Scalar(0), -1);

            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(1, 7));
            Mat close = new Mat();
            Cv2.MorphologyEx(threshEdge, close, MorphTypes.Close, seClose);

            Mat noCircle = new Mat();
            RemoveCircles(close, out noCircle);

            Cv2.Rectangle(noCircle, new Rect(0, 0, threshEdge.Cols, fanghanhouY[0] - 10), new Scalar(0), -1);
            //Cv2.Rectangle(noCircle, new Rect(0, 0, b[1], tonghouY[1]), new Scalar(1), -1);



            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(1, 3));
            Mat open = new Mat();
            Cv2.MorphologyEx(noCircle, open, MorphTypes.Open, seOpen);
            Mat noMin = new Mat();
            GetArea(open, out noMin, 2000, true);
            //GetMaxArea(close, out noMin);
            ImageShow(threshEdge, close * 255, noMin * 255);
            Mat result = noMin.Clone();
            Scalar sum = new Scalar(0);
            for (int j = b[2] - 20; j > 0; j--)
            {
                sum = result[fanghanhouY[0], tonghouY[0] - 20, j - 1, j].Sum();
                //if (result.Get<byte>(tonghouY[0] - 50, j) > 0)
                if ((int)sum > 20)
                {
                    offsetX[0] = j;
                    break;
                }
            }

            offsetX[1] = b[2];
            int compensate = 10;
            offsetX[0] -= compensate;
        }

        /// <summary>
        /// 防焊 没有开口 offset
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="offsetX"></param>
        /// <param name="i"></param>
        public void FanghanOffset5_3(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] offsetX, int i=0)
        {
            offsetX = new int[2];
            //二值化
            Mat threshEdge = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (i*5), 255, ThresholdTypes.BinaryInv);
            //去碎屑
            threshEdge = ~BinaryTools.DebrisRemoval_New(threshEdge.CvtColor(ColorConversionCodes.GRAY2BGRA), 250).CvtColor(ColorConversionCodes.BGRA2GRAY);
            for (int j = b[2] - 55; j > 0; j--)
            {
                if (threshEdge.At<byte>(tonghouY[0]-5, j) == 0)
                {
                    Mat temp = ~threshEdge;
                    if (Cv2.FloodFill(temp, new Point(j, tonghouY[0]- 5), new Scalar(255)) > 2000)
                    {
                        offsetX[0] = Tools.GetLeftOrRightPoint(new Point(j, tonghouY[0] - 5), threshEdge, 2).X - 3;
                        break;
                    }
                }
            }

            offsetX[1] = b[2];

            if (offsetX[0] <= 0 || Math.Abs(offsetX[1] - offsetX[0]) > 800)
            {
                FanghanOffset5_3(gray, tonghouY, b, fanghanhouY, out offsetX, ++i);
            }
        }

        public void FanghanOffset7(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] offsetX, int i=0)
        {
            offsetX = new int[2];
            //二值化
            Mat threshEdge = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (i * 5), 255, ThresholdTypes.BinaryInv);
            //去碎屑
            threshEdge = ~BinaryTools.DebrisRemoval_New(threshEdge.CvtColor(ColorConversionCodes.GRAY2BGRA), 250).CvtColor(ColorConversionCodes.BGRA2GRAY);
            for (int j = b[2] - 55; j > 0; j--)
            {
                if (threshEdge.At<byte>(tonghouY[0] - 5, j) == 0)
                {
                    Mat temp = ~threshEdge;
                    if (Cv2.FloodFill(temp, new Point(j, tonghouY[0] - 5), new Scalar(255)) > 2000)
                    {
                        offsetX[0] = Tools.GetLeftOrRightPoint(new Point(j, tonghouY[0] - 5), threshEdge, 2).X;
                        break;
                    }
                }
            }

            offsetX[1] = b[2];

            if (offsetX[0] <= 0 || Math.Abs(offsetX[1] - offsetX[0]) > 800)
            {
                FanghanOffset7(gray, tonghouY, b, fanghanhouY, out offsetX, ++i);
            }
        }

        

        public void FanhanKaikou3(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] fanghankaikou, int i=0)
        {
            //二值化
            Mat threshEdge = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (i * 3), 255, ThresholdTypes.BinaryInv);
            //去碎屑
            threshEdge = ~BinaryTools.DebrisRemoval_New(threshEdge.CvtColor(ColorConversionCodes.GRAY2BGRA), 3000).CvtColor(ColorConversionCodes.BGRA2GRAY);
            fanghankaikou = new int[2];
            for (int j = b[3]; j < threshEdge.Cols - 1; j++)
            {
                if (threshEdge.At<byte>(tonghouY[0] - 5, j) == 0)
                {
                    Mat temp = ~threshEdge;
                    if (Cv2.FloodFill(temp, new Point(j, tonghouY[0] - 5), new Scalar(255)) > 3000 && Math.Abs(b[3] - j)>20)
                    {
                        //fanghankaikou[1] = j;
                        //Mat edge = threshEdge.Canny(0, 255);
                        fanghankaikou[1] = Tools.GetLeftOrRightPoint(new Point(j, tonghouY[0] - 5), threshEdge, 1).X - 3;
                        break;
                    }
                }
            }

            if(i>=10)
            {
                fanghankaikou[1] = 1200;
            }
            else
            {
                if (fanghankaikou[1] == 0)
                {
                    FanhanKaikou3(gray, tonghouY, b, fanghanhouY, out fanghankaikou, ++i);
                }
            }
        }

        /// <summary>
        /// 計算防焊的LPI厚度
        /// </summary>
        /// <param name="imageRed">原圖紅色通道圖片</param>
        /// <param name="tonghouY">銅厚的上下縱坐標</param>
        /// <param name="b">第一層銅的起始點（橫向），b[0]:銅起始點；b[1]:銅結束點；b[2]:銅再次開始點</param>
        /// <param name="LPIHouduY"></param>
        public void FanghanLPI(Mat imageRed, int[] tonghouY, int[] b, out int[] LPIHouduY)
        {
            int LPIHouduX = b[1] + 100;
            LPIHouduY = new int[2];
            Mat crop = imageRed[tonghouY[0] - 120, tonghouY[0] - 20, LPIHouduX - 10, LPIHouduX + 10];
            Mat thresh = 1 - crop.Threshold(80, 1, ThresholdTypes.Binary);
            Mat seopen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(10, 3));
            Mat open = new Mat();
            Cv2.MorphologyEx(thresh, open, MorphTypes.Open, seopen);
            Cv2.Rectangle(open, new Rect(0, 0, 1, open.Rows), new Scalar(1), -1);
            Cv2.Rectangle(open, new Rect(0, thresh.Rows - 1, thresh.Cols, 1), new Scalar(1), -1);
            Fill(open, out open, 1);
            Cv2.Rectangle(open, new Rect(0, 0, 1, open.Rows), new Scalar(0), -1);
            Mat result;
            GetMaxArea(open, out result);
            //ImageShow(result*255, open * 255);
            Scalar sum = new Scalar(0);
            for (int i = 0; i < result.Rows; i++)
            {
                sum = result[i, i + 1, 0, result.Cols].Sum();
                if ((int)sum > 10)
                {
                    LPIHouduY[0] = i + tonghouY[0] - 120;
                    break;
                }
            }
        }

        

        /// <summary>
        /// 705修改，提取LPI，使用去圆算法
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="LPIHouduY"></param>
        public void FanghanLPI2_2(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] LPIHouduY, int a=0)
        {
            int LPIHouduX = b[1] + 100;
            LPIHouduY = new int[2];
            Mat result1 = gray.Threshold(BinaryTools.CalcSuitableValue(gray)-10 + (a*5), 255, ThresholdTypes.Binary);
            LPIHouduY[0] = tonghouY[1];
            for (int i = LPIHouduY[0] - 120 - Math.Abs(tonghouY[1]- tonghouY[0]); i < LPIHouduY[0] - 50; i++)
            {
                if(result1.At<byte>(i, LPIHouduX) ==0)
                {
                    Mat temp = ~result1;
                    if (Cv2.FloodFill(temp, new Point(LPIHouduX, i), new Scalar(255)) > 3500)
                    {
                        LPIHouduY[1] = i;
                        break;
                    }
                }
            }

            if (LPIHouduY[1] == 0)
            {
                FanghanLPI2_2(gray, tonghouY, b, fanghanhouY, out LPIHouduY, ++a);
            }
        }

        public void FanghanLPI2_3(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] LPIHouduY, int a=0)
        {
            int LPIHouduX = b[1] + 100;
            LPIHouduY = new int[2];
            Mat result1 = gray.Threshold(BinaryTools.CalcSuitableValue(gray) - 10 + (a * 5), 255, ThresholdTypes.Binary);
            LPIHouduY[0] = tonghouY[1];

            for (int i = LPIHouduY[0] - 120 - Math.Abs(tonghouY[1] - tonghouY[0]); i < LPIHouduY[0] - 50; i++)
            {
                if (result1.At<byte>(i, LPIHouduX) == 0)
                {
                    Mat temp = ~result1;
                    if (Cv2.FloodFill(temp, new Point(LPIHouduX, i), new Scalar(255)) > 3500)
                    {
                        LPIHouduY[1] = i;
                        break;
                    }
                }
            }

            if (LPIHouduY[1] == 0)
            {
                FanghanLPI2_3(gray, tonghouY, b, fanghanhouY, out LPIHouduY, ++a);
            }

            /*int LPIHouduX = b[1] + 100;
            LPIHouduY = new int[2];
            //LPI上层
            Mat newGray = new Mat();
            Cv2.GaussianBlur(gray, newGray, new Size(15, 15), 5, 5);
            Mat edge = new Mat();
            Edge(newGray, out edge);
            Mat threshEdge = new Mat();
            threshEdge = edge.Threshold(20, 255, ThresholdTypes.Binary);
            Mat threshEdge1 = threshEdge.Clone();
            Cv2.Rectangle(threshEdge1, new Rect(0, 0, threshEdge.Cols, fanghanhouY[0] - 10), new Scalar(0), -1);
            Cv2.Rectangle(threshEdge1, new Rect(0, tonghouY[0] - 20, threshEdge.Cols, tonghouY[1]), new Scalar(255), -1);
            Cv2.Rectangle(threshEdge1, new Rect(0, tonghouY[1], threshEdge.Cols, threshEdge.Rows - tonghouY[1]), new Scalar(0), -1);
            Mat noCircle = new Mat();
            RemoveCircles(threshEdge1, out noCircle);
            Mat result1 = noCircle.Clone();
            Scalar sum = new Scalar(0);
            for (int i = fanghanhouY[0]<=0?1: fanghanhouY[0]; i < tonghouY[0] - 20; i++)
            {
                sum = result1[i, i + 1, LPIHouduX - 50, LPIHouduX + 50].Sum();
                if ((int)sum > 50)
                {
                    LPIHouduY[0] = i;
                    break;
                }
            }
            if (LPIHouduY[0] == 0)
            {
                for (int i = fanghanhouY[0] <= 0 ? 1 : fanghanhouY[0]; i < tonghouY[0] - 20; i++)
                {
                    sum = result1[i, i + 1, LPIHouduX - 50, LPIHouduX + 50].Sum();
                    if ((int)sum > 30)
                    {
                        LPIHouduY[0] = i;
                        break;
                    }
                }
            }
            //LPI下层
            Mat newGray2 = new Mat();
            Cv2.GaussianBlur(gray, newGray2, new Size(11, 11), 3, 3);
            Mat edge2 = new Mat();
            Edge(newGray2, out edge2);
            Mat threshEdge2 = new Mat();
            threshEdge2 = edge2.Threshold(20, 255, ThresholdTypes.Binary);
            Mat threshEdge3 = threshEdge2.Clone();

            Cv2.Rectangle(threshEdge3, new Rect(0, 0, threshEdge.Cols, fanghanhouY[0]), new Scalar(0), -1);
            Cv2.Rectangle(threshEdge3, new Rect(0, tonghouY[1] + 20, threshEdge.Cols, threshEdge.Rows - tonghouY[1] - 20), new Scalar(0), -1);
            Mat seClose2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 3));
            Mat close2 = new Mat();
            Cv2.MorphologyEx(threshEdge3, close2, MorphTypes.Close, seClose2);
            close2 = close2 / 255;
            Mat result2 = close2.Clone();
            for (int i = tonghouY[1] + 20; i > tonghouY[1] - 20; i--)
            {
                sum = result2[i - 1, i, LPIHouduX - 50, LPIHouduX + 50].Sum();
                if ((int)sum > 80)
                {
                    LPIHouduY[1] = i;
                    break;
                }
            }
            int compensate = 5;
            LPIHouduY[0] += compensate;
            LPIHouduY[1] -= compensate;*/
        }
        /// <summary>
        /// 计算防焊LPI厚度，暂时用在有开口上，从下往上，寻找横向像素点足够多的时候
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="fanghanhouY"></param>
        /// <param name="LPIHouduY"></param>
        public void FanghanLPI3(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] LPIHouduY)
        {
            int LPIHouduX = b[1] + 100;
            LPIHouduY = new int[2];
            //LPI上层
            Mat newGray = new Mat();
            Cv2.GaussianBlur(gray, newGray, new Size(11, 11), 5, 5);
            Mat edge = new Mat();
            Edge(newGray, out edge);
            Mat threshEdge = new Mat();
            threshEdge = edge.Threshold(20, 255, ThresholdTypes.Binary);
            Cv2.Rectangle(threshEdge, new Rect(0, 0, threshEdge.Cols, fanghanhouY[0]), new Scalar(0), -1);
            //Mat seClose = 
            Mat noMin = new Mat();
            GetArea(threshEdge, out noMin, 1000, true);
            //ImageShow(edge, threshEdge, noMin * 255);
            Mat result = noMin.Clone();
            Scalar sum1 = new Scalar(0);
            for (int i = tonghouY[0]; i > fanghanhouY[0]; i--)
            {
                sum1 = result[i - 1, i, LPIHouduX - 50, LPIHouduX + 50].Sum();
                if ((int)sum1 > 50)
                {
                    LPIHouduY[0] = i;
                    break;
                }
            }
            //LPI下层
            Mat newGray2 = new Mat();
            Cv2.GaussianBlur(gray, newGray2, new Size(11, 11), 3, 3);
            Mat edge2 = new Mat();
            Edge(newGray2, out edge2);
            Mat threshEdge2 = new Mat();
            threshEdge2 = edge2.Threshold(20, 255, ThresholdTypes.Binary);
            //Mat fill = new Mat();
            //Fill(threshEdge2, out fill, 255);
            Mat threshEdge3 = threshEdge2.Clone();

            Cv2.Rectangle(threshEdge3, new Rect(0, 0, threshEdge.Cols, fanghanhouY[0]), new Scalar(0), -1);
            Cv2.Rectangle(threshEdge3, new Rect(0, tonghouY[1] + 20, threshEdge.Cols, threshEdge.Rows - tonghouY[1] - 20), new Scalar(0), -1);
            //Mat seClose2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 3));
            //Mat close2 = new Mat();
            //Cv2.MorphologyEx(threshEdge3, close2, MorphTypes.Close, seClose2);
            Mat noMin2 = new Mat();
            GetArea(threshEdge3, out noMin2, 2000, true);
            //ImageShow(edge2, threshEdge2, noMin2 * 255);
            Mat result2 = noMin2.Clone();
            Scalar sum = new Scalar(0);
            for (int i = tonghouY[1] + 20; i > tonghouY[1] - 20; i--)
            {
                sum = result2[i - 1, i, LPIHouduX - 50, LPIHouduX + 50].Sum();
                if ((int)sum > 80)
                //if (result2.Get<byte>(i, LPIHouduX) > 0)
                {
                    LPIHouduY[1] = i;
                    break;
                }
            }
            int compensate1 = 5;
            LPIHouduY[0] -= compensate1;
            int compensate2 = 5;
            LPIHouduY[1] -= compensate2;
        }
        public void FanghanLPI4(Mat gray, int[] tonghouY, int[] b, int[] fanghanhouY, out int[] LPIHouduY)
        {
            int LPIHouduX = b[1] + 100;
            LPIHouduY = new int[2];
            //LPI上层
            Mat newGray = new Mat();
            Cv2.GaussianBlur(gray, newGray, new Size(11, 11), 5, 5);
            Mat edge = new Mat();
            Edge(newGray, out edge);
            Mat threshEdge = new Mat();
            threshEdge = edge.Threshold(20, 255, ThresholdTypes.Binary);
            Cv2.Rectangle(threshEdge, new Rect(0, 0, threshEdge.Cols, fanghanhouY[0] - 10), new Scalar(0), -1);
            //Mat seClose = 
            Mat noMin = new Mat();
            GetArea(threshEdge, out noMin, 1000, true);
            ImageShow(edge, threshEdge, noMin * 255);
            Mat result = noMin.Clone();
            Scalar sum1 = new Scalar(0);
            for (int i = tonghouY[0]; i > fanghanhouY[0]; i--)
            {
                sum1 = result[i - 1, i, LPIHouduX - 50, LPIHouduX + 50].Sum();
                if ((int)sum1 > 50)
                {
                    LPIHouduY[0] = i;
                    break;
                }
            }
            //LPI下层
            Mat newGray2 = new Mat();
            Cv2.GaussianBlur(gray, newGray2, new Size(11, 11), 3, 3);
            Mat edge2 = new Mat();
            Edge(newGray2, out edge2);
            Mat threshEdge2 = new Mat();
            threshEdge2 = edge2.Threshold(20, 255, ThresholdTypes.Binary);
            //Mat fill = new Mat();
            //Fill(threshEdge2, out fill, 255);
            Mat threshEdge3 = threshEdge2.Clone();

            Cv2.Rectangle(threshEdge3, new Rect(0, 0, threshEdge.Cols, fanghanhouY[0]), new Scalar(0), -1);
            Cv2.Rectangle(threshEdge3, new Rect(0, tonghouY[1] + 20, threshEdge.Cols, threshEdge.Rows - tonghouY[1] - 20), new Scalar(0), -1);
            //Mat seClose2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 3));
            //Mat close2 = new Mat();
            //Cv2.MorphologyEx(threshEdge3, close2, MorphTypes.Close, seClose2);
            Mat noMin2 = new Mat();
            GetArea(threshEdge3, out noMin2, 2000, true);
            //ImageShow(edge2, threshEdge2, noMin2 * 255);
            Mat result2 = noMin2.Clone();
            Scalar sum = new Scalar(0);
            for (int i = tonghouY[1] + 20; i > tonghouY[1] - 20; i--)
            {
                sum = result2[i - 1, i, LPIHouduX - 50, LPIHouduX + 50].Sum();
                if ((int)sum > 80)
                //if (result2.Get<byte>(i, LPIHouduX) > 0)
                {
                    LPIHouduY[1] = i;
                    break;
                }
            }
            int compensate1 = 5;
            LPIHouduY[0] -= compensate1;
            int compensate2 = 5;
            LPIHouduY[1] -= compensate2;
        }
        /// <summary>
        /// 計算防焊的undercut
        /// </summary>
        /// <param name="imageRed">原圖紅色通道圖片</param>
        /// <param name="tonghouY">銅厚的上下縱坐標</param>
        /// <param name="b">第一層銅的起始點（橫向），b[0]:銅起始點；b[1]:銅結束點；b[2]:銅再次開始點</param>
        /// <param name="undercutX">輸出防焊同第三条线的交点之间的水平距离</param>
        public void FanghanUndercut(Mat imageRed, int[] tonghouY, int[] b, int[] offsetX, out int undercutX)
        {
            int compensate = 20;
            undercutX = 0;
            Mat crop = imageRed[tonghouY[0] - 100, tonghouY[1] + 20, b[1] + 20, offsetX[0]];
            Mat thresh = new Mat();
            double t = Cv2.Threshold(crop, thresh, 0, 1, ThresholdTypes.Otsu);
            thresh = 1 - crop.Threshold(t - 30, 1, ThresholdTypes.Otsu);

            Cv2.Rectangle(thresh, new Rect(0, 0, 20, thresh.Rows - 1), new Scalar(1), -1);

            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Mat close = new Mat();
            Cv2.MorphologyEx(thresh, close, MorphTypes.Close, se);
            Mat fill = new Mat();
            Fill(close, out fill, 1);
            Mat result = fill;
            GetMaxContour(result, out result);
            //ImageShow(result * 255);
            Mat se2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(1, 5));
            Mat dilate = new Mat();
            Cv2.Dilate(result, dilate, se2);
            //ImageShow(close * 255, dilate * 255);
            result = dilate;
            Scalar sum = new Scalar(0);
            Scalar max = new Scalar(0);
            int upper = 0;
            for (int i = 120; i < crop.Rows - 10; i++)
            {
                sum = result[i, i + 1, 0, result.Cols].Sum();
                if ((int)sum > (int)max)
                {
                    max = sum;
                    upper = i;
                }
            }

            for (int j = result.Cols - 20; j > 20; j--)
            {
                if (result.Get<byte>(upper, j) > 0)
                {
                    undercutX = j + b[1] + 20 - compensate;
                    break;
                }
            }
        }
        /// <summary>
        /// 计算防焊没开口undercut
        /// </summary>
        /// <param name="image">原图</param>
        /// <param name="tonghouY">铜厚纵坐标</param>
        /// <param name="b">铜的边界</param>
        /// <param name="offsetX"></param>
        /// <param name="undercutX">输出undercut位置</param>
        public void FanghanUndercut2(Mat image, int[] tonghouY, int[] b, int[] offsetX, out int undercutX)
        {
            /*
             * 利用canny边缘检测，闭运算连接后，填充，保留大面积，取反，关键部位每列和为1时记录
             */
            undercutX = 0;
            Cv2.GaussianBlur(image, image, new Size(7, 7), 3, 3);
            Mat edge = new Mat();
            Cv2.Canny(image, edge, 10, 15);
            //ceju.ImageShow(edge);
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
            Mat close = new Mat();
            Cv2.MorphologyEx(edge, close, MorphTypes.Close, se);
            Mat fill = new Mat();
            Fill(close, out fill, 255);
            //ImageShow(edge, close, fill);
            Mat draw = new Mat();
            GetArea(close, out draw, 10000, true);
            //ImageShow(draw * 255);
            Mat result = 1 - draw;
            Mat crop = result[tonghouY[0] + 20, tonghouY[1] + 10, b[1] + 20, b[2]].Clone();
            GetMaxArea(crop, out crop);
            //ImageShow(crop * 255);
            Scalar sum = new Scalar(0);
            for (int j = 0; j < crop.Cols; j++)
            {
                sum = crop[0, crop.Rows, j, j + 1].Sum();
                if ((int)sum > 0)
                {
                    undercutX = j + b[1] + 20;
                    break;
                }
            }
            int compensate = 25;
            undercutX -= compensate;
        }
        public void FanghanUndercut3(Mat gray, int[] tonghouY, int[] b, int[] offsetX, int[] fanghanhouY, out int undercutX)
        {
            undercutX = 0;
            Mat filter = new Mat();
            PointEnhancement(gray, out filter);
            Mat newGray = new Mat();
            Cv2.GaussianBlur(filter, newGray, new Size(11, 11), 5, 5);
            Mat edge = new Mat();
            Edge(newGray, out edge);
            Mat threshEdge = new Mat();
            threshEdge = edge.Threshold(20, 255, ThresholdTypes.Binary);
            Mat fill = new Mat();
            Fill(threshEdge, out fill, 255);

            Cv2.Rectangle(fill, new Rect(0, 0, threshEdge.Cols, fanghanhouY[0]), new Scalar(0), -1);
            //Cv2.Rectangle(threshEdge, new Rect(0, 0, b[1], tonghouY[1]), new Scalar(255), -1);
            Cv2.Rectangle(fill, new Rect(0, tonghouY[1] + 20, threshEdge.Cols, threshEdge.Rows - tonghouY[1] - 20), new Scalar(0), -1);
            //Cv2.Rectangle(threshEdge, new Rect(offsetX[0], 0, threshEdge.Cols-offsetX[0], threshEdge.Rows), new Scalar(0), -1);
            //Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 1));
            //Mat close = new Mat();
            //Cv2.MorphologyEx(threshEdge, close, MorphTypes.Close, seClose);
            Mat max = new Mat();
            //GetMaxArea(close, out max);
            GetArea(fill, out max, 2000, true);
            Mat fanse = 1 - max;
            ImageShow(threshEdge, fill, max * 255, fanse * 255);
            Mat result = fanse.Clone();
            Scalar sum = new Scalar(0);
            int lowerBound = 0, upperBound = 0;
            int leftBound = (offsetX[0] - 130 > b[1] + 20) ? offsetX[0] - 130 : b[1] + 20;
            for (int i = tonghouY[0]; i < tonghouY[1] + 20; i++)
            {
                sum = result[i, i + 1, leftBound, offsetX[0] - 20].Sum();
                if ((int)sum == 0)
                {
                    upperBound = i;
                    break;
                }
            }
            for (int i = tonghouY[1] + 20; i > tonghouY[0]; i--)
            {
                sum = result[i - 1, i, leftBound, offsetX[0] - 20].Sum();
                if ((int)sum == 0)
                {
                    lowerBound = i;
                    break;
                }
            }
            //Cv2.Line(fanse, new Point(leftBound,upperBound), new Point(leftBound,lowerBound), new Scalar(1), 2, LineTypes.Link8);
            //ImageShow(fanse*255);
            for (int j = leftBound; j < offsetX[0]; j++)
            {
                sum = result[upperBound, lowerBound, j, j + 1].Sum();
                if ((int)sum > 0)
                {
                    undercutX = j;
                    break;
                }
            }
            int compensate = 30;
            undercutX -= compensate;
        }
        public void FanghanUndercut4(Mat gray, int[] tonghouY, int[] b, int[] offsetX, int[] LPIHouY, out int undercutX)
        {
            undercutX = 0;
            Mat newGray = new Mat();
            Cv2.GaussianBlur(gray, newGray, new Size(15, 15), 5, 5);
            Mat edge = new Mat();
            Edge(newGray, out edge);
            Mat threshEdge = new Mat();
            threshEdge = edge.Threshold(30, 255, ThresholdTypes.Binary);
            Mat threshEdge1 = threshEdge.Clone();
            Cv2.Rectangle(threshEdge1, new Rect(0, 0, b[1] + 20, threshEdge1.Rows), new Scalar(255), -1);
            Mat noMin = new Mat();
            GetArea(threshEdge1, out noMin, 50000, true);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
            Mat close = new Mat();
            Cv2.MorphologyEx(noMin, close, MorphTypes.Close, seClose);
            //ImageShow(threshEdge1, noMin * 255,close*255);
            int[] x1 = new int[10];
            int[] y1 = new int[10];
            int count = 0;
            for (int i = tonghouY[0] + 20; i < tonghouY[0] + 30; i++)
            {
                for (int j = offsetX[0] + 30; j > offsetX[0] - 100; j--)
                {
                    if (close.Get<byte>(i, j) > 0)
                    {
                        x1[count] = j;
                        y1[count] = i;
                        count++;
                        break;
                    }
                }
                if (count == 10)
                    break;
            }
            int[] x2 = new int[10];
            int[] y2 = new int[10];
            count = 0;
            for (int i = tonghouY[0] + 30; i < tonghouY[0] + 40; i++)
            {
                for (int j = offsetX[0] + 30; j > offsetX[0] - 100; j--)
                {
                    if (close.Get<byte>(i, j) > 0)
                    {
                        x2[count] = j;
                        y2[count] = i;
                        count++;
                        break;
                    }
                }
                if (count == 10)
                    break;
            }
            double[] averOrdinate1 = new double[2];
            double[] averOrdinate2 = new double[2];
            AverOrdinate(x1, y1, out averOrdinate1);
            AverOrdinate(x2, y2, out averOrdinate2);
            LineShow(gray, (int)averOrdinate1[0], (int)averOrdinate1[1], (int)averOrdinate2[0], (int)averOrdinate2[1]);
            //ImageShow(gray);
            double slope = ((averOrdinate2[0] - averOrdinate1[0]) == 0) ? 0 : (averOrdinate2[1] - averOrdinate1[1]) / (averOrdinate2[0] - averOrdinate1[0]);
            double intercept = averOrdinate1[1] - slope * averOrdinate1[0];
            undercutX = (slope == 0) ? 0 : (int)((LPIHouY[1] - intercept) / slope);

            int compensate = 10;
            undercutX -= compensate;
        }
        /// <summary>
        /// 提取undercut，由于有开口亮度和对比对低，参数不同。
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="offsetX"></param>
        /// <param name="LPIHouY"></param>
        /// <param name="undercutX"></param>
        public void FanghanUndercut5(Mat gray, int[] tonghouY, int[] b, int[] offsetX, int[] LPIHouY, out int undercutX)
        {
            undercutX = 0;
            Mat newGray = new Mat();
            Cv2.GaussianBlur(gray, newGray, new Size(15, 15), 5, 5);
            Mat edge = new Mat();
            Edge(newGray, out edge);
            Mat threshEdge = new Mat();
            threshEdge = edge.Threshold(25, 255, ThresholdTypes.Binary);
            Mat threshEdge1 = threshEdge.Clone();
            Cv2.Rectangle(threshEdge1, new Rect(0, 0, b[1] + 20, threshEdge1.Rows), new Scalar(255), -1);
            Mat noMin = new Mat();
            GetArea(threshEdge1, out noMin, 2000, true);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
            Mat close = new Mat();
            Cv2.MorphologyEx(noMin, close, MorphTypes.Close, seClose);
            //ImageShow(threshEdge1, noMin * 255, close * 255);
            #region//获取平均坐标
            int[] x1 = new int[10];
            int[] y1 = new int[10];
            int count = 0;
            for (int i = tonghouY[0] - 20; i < tonghouY[0] - 10; i++)
            {
                for (int j = offsetX[0] + 20; j > offsetX[0] - 100; j--)
                {
                    if (close.Get<byte>(i, j) > 0)
                    {
                        x1[count] = j;
                        y1[count] = i;
                        count++;
                        break;
                    }
                }
                if (count == 10)
                    break;
            }
            int[] x2 = new int[10];
            int[] y2 = new int[10];
            count = 0;
            for (int i = tonghouY[0]; i < tonghouY[0] + 10; i++)
            {
                for (int j = offsetX[0] + 20; j > offsetX[0] - 100; j--)
                {
                    if (close.Get<byte>(i, j) > 0)
                    {
                        x2[count] = j;
                        y2[count] = i;
                        count++;
                        break;
                    }
                }
                if (count == 10)
                    break;
            }
            double[] averOrdinate1 = new double[2];
            double[] averOrdinate2 = new double[2];
            AverOrdinate(x1, y1, out averOrdinate1);
            AverOrdinate(x2, y2, out averOrdinate2);
            #endregion
            //LineShow(gray, (int)averOrdinate1[0], (int)averOrdinate1[1], (int)averOrdinate2[0], (int)averOrdinate2[1]);
            //ImageShow(gray,close*255);
            double slope = ((averOrdinate2[0] - averOrdinate1[0]) == 0) ? 0 : (averOrdinate2[1] - averOrdinate1[1]) / (averOrdinate2[0] - averOrdinate1[0]);
            double intercept = averOrdinate1[1] - slope * averOrdinate1[0];
            undercutX = (slope == 0) ? 0 : (int)((LPIHouY[1] - intercept) / slope);

            int compensate = 10;
            undercutX -= compensate;
        }
        public void FanghanUndercut5_2(Mat gray, int[] tonghouY, int[] b, int[] offsetX, int[] LPIHouY, out int undercutX, int i=0)
        {
            undercutX = 0;
            Mat filter = new Mat();
            PointEnhancement(gray, out filter);
            Mat newGray = new Mat();
            Cv2.GaussianBlur(filter, newGray, new Size(15, 15), 5, 5);

            Mat threshEdge = newGray.Threshold(BinaryTools.CalcSuitableValueForUnderCut(gray) - 15 + (i * 5), 255, ThresholdTypes.BinaryInv);
            Mat result = threshEdge.Canny(0, 255);

            int tempRange = (offsetX[0] - 300) <= 0 ? 1 : offsetX[0] - 300;
            //想左找
            for (int j = offsetX[0] + 10; j > tempRange; j--)
            {
                byte v = result.Get<byte>(tonghouY[1] - 20, j);
                if (v > 0)
                {
                    if(Cv2.FloodFill(result, new Point(j, tonghouY[0] - 20), new Scalar(255)) > 300)
                    {
                        undercutX = Tools.GetLeftPoint(new Point(j, tonghouY[1] - 20), result).X;
                        break;
                    }
                }
            }

            if (i > 10)
                undercutX = offsetX[0] - 25;
            else
            {
                if (undercutX == 0 || (undercutX > 0 && offsetX[0] - undercutX > 100))
                {
                    FanghanUndercut5_2(gray, tonghouY, b, offsetX, LPIHouY, out undercutX, ++i);
                }
            }
        }
        /// <summary>
        /// 防焊双层铜undercut，采集点位置不同
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="offsetX"></param>
        /// <param name="LPIHouY"></param>
        /// <param name="undercutX"></param>
        public void FanghanUndercut6(Mat gray, int[] tonghouY, int[] b, int[] offsetX, int[] LPIHouY, out int undercutX)
        {
            undercutX = 0;
            Mat newGray = new Mat();
            Cv2.GaussianBlur(gray, newGray, new Size(15, 15), 5, 5);
            Mat edge = new Mat();
            Edge(newGray, out edge);
            Mat threshEdge = new Mat();
            threshEdge = edge.Threshold(25, 255, ThresholdTypes.Binary);
            Mat threshEdge1 = threshEdge.Clone();
            Cv2.Rectangle(threshEdge1, new Rect(0, 0, b[1] + 20, threshEdge1.Rows), new Scalar(255), -1);
            Mat noMin = new Mat();
            GetArea(threshEdge1, out noMin, 2000, true);
            //Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
            //Mat close = new Mat();
            //Cv2.MorphologyEx(noMin, close, MorphTypes.Close, seClose);
            Mat result = noMin.Clone();
            //ImageShow(threshEdge1, noMin * 255/*, close * 255*/);
            int[] x1 = new int[10];
            int[] y1 = new int[10];
            int count = 0;
            for (int i = tonghouY[0] - 10; i < tonghouY[0]; i += 1)
            {
                for (int j = offsetX[0] + 20; j > offsetX[0] - 100; j--)
                {
                    if (result.Get<byte>(i, j) > 0)
                    {
                        x1[count] = j;
                        y1[count] = i;
                        count++;
                        break;
                    }
                }
                if (count == 10)
                    break;
            }
            int[] x2 = new int[10];
            int[] y2 = new int[10];
            count = 0;
            for (int i = tonghouY[0] + 10; i < tonghouY[0] + 20; i += 1)
            {
                for (int j = offsetX[0] + 20; j > offsetX[0] - 100; j--)
                {
                    if (result.Get<byte>(i, j) > 0)
                    {
                        x2[count] = j;
                        y2[count] = i;
                        count++;
                        break;
                    }
                }
                if (count == 10)
                    break;
            }
            double[] averOrdinate1 = new double[2];
            double[] averOrdinate2 = new double[2];
            AverOrdinate(x1, y1, out averOrdinate1);
            AverOrdinate(x2, y2, out averOrdinate2);
            //LineShow(gray, (int)averOrdinate1[0], (int)averOrdinate1[1], (int)averOrdinate2[0], (int)averOrdinate2[1]);
            //ImageShow(gray);
            double slope = ((averOrdinate2[0] - averOrdinate1[0]) == 0) ? 0 : (averOrdinate2[1] - averOrdinate1[1]) / (averOrdinate2[0] - averOrdinate1[0]);
            double intercept = averOrdinate1[1] - slope * averOrdinate1[0];
            undercutX = (slope == 0) ? 0 : (int)((LPIHouY[1] - intercept) / slope);

            int compensate = 10;
            undercutX -= compensate;
        }
        /// <summary>
        /// 705改，提取undercut
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tonghouY"></param>
        /// <param name="b"></param>
        /// <param name="offsetX"></param>
        /// <param name="LPIHouY"></param>
        /// <param name="undercutX"></param>
        public void FanghanUndercut6_2(Mat gray, int[] tonghouY, int[] b, int[] offsetX, int[] LPIHouY, out int undercutX)
        {
            undercutX = 0;
            Mat filter = new Mat();
            PointEnhancement(gray, out filter);
            Mat newGray = new Mat();
            Cv2.GaussianBlur(filter, newGray, new Size(15, 15), 5, 5);

            //PointEnhancement(gray, out gray);
            //Mat crop = gray[tonghouY[0] - 120, tonghouY[0] - 20, LPIHouduX - 10, LPIHouduX + 10];
            Mat edge = new Mat();
            //Sobel(gray, out edge);
            Edge(newGray, out edge);
            Mat threshEdge = new Mat();
            threshEdge = edge.Threshold(25, 255, ThresholdTypes.Binary);

            //Cv2.Rectangle(threshEdge, new Rect(0, tonghouY[0]-100, b[1], tonghouY[1]-tonghouY[0]+100), new Scalar(255), -1);

            Mat noCircle = new Mat();
            RemoveCircles(threshEdge, out noCircle);

            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
            Mat close = new Mat();
            Cv2.MorphologyEx(noCircle, close, MorphTypes.Close, seClose);

            //Mat noMin = new Mat();
            //GetArea(threshEdge1, out noMin, 2000, true);
            //Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
            //Mat close = new Mat();
            //Cv2.MorphologyEx(noMin, close, MorphTypes.Close, seClose);
            Mat result = close.Clone();
            //ImageShow(threshEdge, noCircle * 255, close * 255);
            int[] x1 = new int[10];
            int[] y1 = new int[10];
            int count = 0;
            for (int i = tonghouY[0] - 10; i < tonghouY[0]; i += 1)
            {
                for (int j = offsetX[0] + 20; j > offsetX[0] - 100; j--)
                {
                    if (result.Get<byte>(i, j) > 0)
                    {
                        x1[count] = j;
                        y1[count] = i;
                        count++;
                        break;
                    }
                }
                if (count == 10)
                    break;
            }
            int[] x2 = new int[10];
            int[] y2 = new int[10];
            count = 0;
            for (int i = tonghouY[0] + 10; i < tonghouY[0] + 20; i += 1)
            {
                for (int j = offsetX[0] + 20; j > offsetX[0] - 100; j--)
                {
                    if (result.Get<byte>(i, j) > 0)
                    {
                        x2[count] = j;
                        y2[count] = i;
                        count++;
                        break;
                    }
                }
                if (count == 10)
                    break;
            }
            double[] averOrdinate1 = new double[2];
            double[] averOrdinate2 = new double[2];
            AverOrdinate(x1, y1, out averOrdinate1);
            AverOrdinate(x2, y2, out averOrdinate2);
            //LineShow(gray, (int)averOrdinate1[0], (int)averOrdinate1[1], (int)averOrdinate2[0], (int)averOrdinate2[1]);
            //ImageShow(gray);
            double slope = ((averOrdinate2[0] - averOrdinate1[0]) == 0) ? 0 : (averOrdinate2[1] - averOrdinate1[1]) / (averOrdinate2[0] - averOrdinate1[0]);
            double intercept = averOrdinate1[1] - slope * averOrdinate1[0];
            undercutX = (slope == 0) ? 0 : (int)((LPIHouY[1] - intercept) / slope);

            int compensate = 10;
            undercutX -= compensate;
        }

        
        //高度差
        /// <summary>
        /// 計算含非零點數最大列
        /// </summary>
        /// <param name="image"></param>
        /// <param name="maxCol"></param>
        public void MaxCol(Mat image, out int maxCol)
        {
            maxCol = 0;
            Scalar sum = new Scalar(0);
            Scalar max = new Scalar(0);
            for (int j = 0; j < image.Cols; j++)
            {
                sum = image[0, image.Rows, j, j + 1].Sum();
                if ((int)sum > (int)max)
                {
                    max = sum;
                    maxCol = j;
                }
            }
        }
        /// <summary>
        /// 得到高度差左右的测量区域
        /// </summary>
        /// <param name="thresh">二值图</param>
        /// <param name="BX">高度差B横坐标</param>
        /// <param name="B_X">高度差B*横坐标</param>
        /// <param name="direction">方向，“left”;"right"</param>
        public void GaoduchaGetDataArea(Mat thresh, out Mat result, out int BX, out int B_X, string direction)
        {
            BX = 0;
            B_X = 0;
            GetMaxArea(thresh, out thresh);
            int[] b = new int[3];
            MaxCol(thresh, out b[1]);
            //ceju.ImageShow(thresh * 255);
            double ordinate1 = 0;
            double ordinate2 = 0;
            switch (direction)
            {
                case "left":
                    ExtractLines(thresh, out ordinate1, b[1] - 500, b[1] - 400, 1);
                    ExtractLines(thresh, out ordinate2, b[1] - 500, b[1] - 400, ordinate1, -1);
                    break;
                case "right":
                    ExtractLines(thresh, out ordinate1, b[1] + 400, b[1] + 500, 1);
                    ExtractLines(thresh, out ordinate2, b[1] + 400, b[1] + 500, ordinate1, -1);
                    break;
            }
            int[] firstAndTwo = new int[] { (int)ordinate1, (int)ordinate2 };

            //int border = 0;
            //switch (direction)
            //{
            //    case "left":
            //        for (int j = b[1]; j>0;j--)
            //        {
            //            if ((int)thresh[(int)ordinate1, (int)ordinate2, j - 1, j].Sum() == 0)
            //            {
            //                border = j;
            //                break;
            //            }
            //        }
            //        break;
            //    case "right":
            //        for (int j = b[1]; j < thresh.Cols; j++)
            //        {
            //            if ((int)thresh[(int)ordinate1, (int)ordinate2, j - 1, j].Sum() == 0)
            //            {
            //                border = j;
            //                break;
            //            }
            //        }
            //        break;
            //}


            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Mat open = new Mat();
            Cv2.MorphologyEx(thresh, open, MorphTypes.Open, se);
            result = open.Clone();
            //ceju.ImageShow(open * 255);
            Scalar sum = new Scalar(0);
            Scalar lastSum = new Scalar(0);
            switch (direction)
            {
                case "left":
                    for (int j = b[1] - 600; j > 0; j -= 5)
                    {
                        sum = open[0, (int)ordinate2, j - 10, j].Sum();
                        if (((int)lastSum - (int)sum) > 60 && (int)lastSum != 0)//不用绝对值差防止凸起
                        {
                            b[0] = j;
                            break;
                        }
                        lastSum = sum;
                    }
                    if (b[0] == 0)
                    {
                        lastSum = 0;
                        sum = 0;
                        for (int j = b[1] - 600; j > 0; j -= 5)
                        {
                            sum = open[0, (int)ordinate2, j - 10, j].Sum();
                            if ((int)lastSum - (int)sum > 20 && (int)lastSum != 0)
                            {
                                b[0] = j;
                                break;
                            }
                            lastSum = sum;
                        }
                    }
                    B_X = b[0] + 15;
                    BX = b[0] + 50;
                    break;
                case "right":
                    for (int j = b[1] + 500; j < open.Cols; j += 5)
                    {
                        sum = open[0, (int)ordinate2, j - 10, j].Sum();
                        if (Math.Abs((int)sum - (int)lastSum) > 50/*80*/ && (int)lastSum != 0
                            && Math.Abs((int)lastSum - (int)(open[0, (int)ordinate2, j + 0, j + 10].Sum())) > 50
                            && (int)sum - (int)(open[0, (int)ordinate2, j + 10, j + 20].Sum()) > 30)
                        {
                            b[2] = j;
                            break;
                        }
                        lastSum = sum;
                    }
                    B_X = b[2] - 15;
                    BX = b[2] - 50;
                    break;
            }


        }
        /// <summary>
        /// 计算高度差左右的测量线的纵坐标
        /// </summary>
        /// <param name="image">测量区域时的结果图</param>
        /// <param name="imageRed">红色通道图</param>
        /// <param name="BY">高度差B纵坐标坐标</param>
        /// <param name="B_Y">高度差B*纵坐标坐标</param>
        /// <param name="BX">高度差B横坐标</param>
        /// <param name="B_X">高度差B*横坐标</param>
        public void GaoduchaB(Mat image, Mat imageRed, out int[] BY, out int[] B_Y, int BX, int B_X)
        {
            BY = new int[2];
            B_Y = new int[2];
            for (int i = 0; i < image.Rows; i++)
            {
                if (image.Get<byte>(i, B_X) > 0)
                {
                    B_Y[1] = i;
                    break;
                }
            }
            for (int i = 0; i < image.Rows; i++)
            {
                if (image.Get<byte>(i, BX) > 0)
                {
                    BY[1] = i;
                    break;
                }
            }
            //Cv2.EqualizeHist(imageRed, imageRed);
            Mat crop = imageRed[BY[1] - 60, BY[1] - 10, B_X - 5, BX + 5];
            Mat thresh2 = 1 - crop.Threshold(0, 1, ThresholdTypes.Otsu);
            //Mat thresh2 = new Mat();
            //double t2 = Cv2.Threshold(crop, thresh2, 0, 1, ThresholdTypes.Otsu);
            //thresh = 1 - crop.Threshold(t + 10, 1, ThresholdTypes.Binary);
            Mat se2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Cv2.MorphologyEx(thresh2, thresh2, MorphTypes.Close, se2);
            GetMaxArea(thresh2, out thresh2);
            //ceju.ImageShow(thresh2 * 255);
            for (int i = 0; i < thresh2.Rows; i++)
            //for (int i = thresh2.Rows-5; i >0;i--)
            {
                if (thresh2.Get<byte>(i, 5) > 0)
                {
                    B_Y[0] = i + BY[1] - 60 + 5;
                    break;
                }
            }
            for (int i = 0; i < thresh2.Rows; i++)
            //for (int i = thresh2.Rows - 5; i > 0; i--)
            {
                if (thresh2.Get<byte>(i, thresh2.Cols - 5) > 0)
                {
                    BY[0] = i + BY[1] - 60 + 5;
                    break;
                }
            }
        }
        /// <summary>
        /// 计算高度差纵坐标
        /// </summary>
        /// <param name="thresh"></param>
        /// <param name="crop"></param>
        /// <param name="BY"></param>
        /// <param name="B_Y"></param>
        /// <param name="BX"></param>
        /// <param name="B_X"></param>
        public void GaoduchaBOrdinateY(Mat thresh, Mat image, out int[] BY, out int[] B_Y, int BX, int B_X)
        {
            BY = new int[2];
            B_Y = new int[2];
            //计算下纵坐标
            for (int i = 0; i < thresh.Rows; i++)
            {
                if (thresh.Get<byte>(i, B_X) > 0)
                {
                    B_Y[1] = i;
                    break;
                }
            }
            for (int i = 0; i < thresh.Rows; i++)
            {
                if (thresh.Get<byte>(i, BX) > 0)
                {
                    BY[1] = i;
                    break;
                }
            }
            //边缘检测
            Mat edge = new Mat();
            //PointEnhancement(image, out image);
            Cv2.GaussianBlur(image, image, new Size(9, 9), 5, 5);

            Cv2.Canny(image, edge, 15, 0);
            //Mat crop = edge[B_Y[1]-60, edge.Rows, B_X - 5, BX + 5].Clone();
            //Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 1));
            //Mat open = new Mat();
            //Cv2.MorphologyEx(edge, open, MorphTypes.Open, seOpen);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 3));
            Mat close = new Mat();
            Cv2.MorphologyEx(edge, close, MorphTypes.Close, seClose);
            //Cv2.MorphologyEx(close, close, MorphTypes.Close, seClose);
            //Cv2.Rectangle(close, new Rect(B_X-5, B_Y[1]-60, 1, close.Rows-(B_Y[1]-60)), new Scalar(255), -1);
            //Cv2.Rectangle(close, new Rect(BX+5, B_Y[1] - 60, 1, close.Rows - (B_Y[1] - 60)), new Scalar(255), -1);
            Mat fill = new Mat();
            Fill(close, out fill, 255);
            Mat maxFill = new Mat();
            //Cv2.Rectangle(fill, new Rect(B_X - 5, B_Y[0] - 60, 1, close.Rows - (B_Y[0] - 60)), new Scalar(0), -1);
            //Cv2.Rectangle(fill, new Rect(BX + 5, B_Y[0] - 60, 1, close.Rows - (B_Y[0] - 60)), new Scalar(0), -1);
            //GetMaxArea(fill, out maxFill);
            GetArea(fill, out maxFill, 150, true);
            //ImageShow(edge, close, fill, maxFill * 255);
            //计算上纵坐标
            for (int i = B_Y[1] - 10; i > 0; i--)
            {
                if (maxFill.Get<byte>(i, B_X) > 0)
                {
                    B_Y[0] = i;
                    break;
                }
            }
            for (int i = BY[1] - 10; i > 0; i--)
            {
                if (maxFill.Get<byte>(i, BX) > 0)
                {
                    BY[0] = i;
                    break;
                }
            }
            int compensate = 5;
            BY[0] -= compensate;
            B_Y[0] -= compensate;
        }
        public void GaoduchaBOrdinateY2(Mat thresh, Mat imageRed, Mat image, out int[] BY, out int[] B_Y, int BX, int B_X, string direction)
        {
            BY = new int[2];
            B_Y = new int[2];
            //计算下纵坐标
            for (int i = 0; i < thresh.Rows; i++)
            {
                if (thresh.Get<byte>(i, B_X) > 0)
                {
                    B_Y[1] = i;
                    break;
                }
            }
            for (int i = 0; i < thresh.Rows; i++)
            {
                if (thresh.Get<byte>(i, BX) > 0)
                {
                    BY[1] = i;
                    break;
                }
            }

            #region//法一
            //边缘检测
            Mat sobelEdge = new Mat();
            //PointEnhancement(image, out image);
            Cv2.GaussianBlur(imageRed, imageRed, new Size(9, 9), 3, 3);
            PointEnhancement(imageRed, out imageRed);
            Sobel(imageRed, out sobelEdge);
            Mat threshEdge = new Mat();
            double t = Cv2.Threshold(sobelEdge, threshEdge, 0, 255, ThresholdTypes.Otsu);
            if (t < 50)
                threshEdge = sobelEdge.Threshold(10, 255, ThresholdTypes.Binary);
            //Mat cannyEdge = new Mat();
            //Cv2.GaussianBlur(image, image, new Size(9, 9), 5, 5);
            //Cv2.Canny(image, cannyEdge, 15, 0);
            //Mat edge = cannyEdge/2 + threshEdge / 2;
            //Cv2.ConvertScaleAbs(edge, edge);
            //横向连接
            Mat text2 = new Mat();
            switch (direction)
            {
                case "left":
                    text2 = threshEdge[B_Y[1] - 40, B_Y[1] - 10, B_X, BX] / 255;
                    break;
                case "right":
                    text2 = threshEdge[B_Y[1] - 40, B_Y[1] - 10, BX, B_X] / 255;
                    break;
            }
            Mat seClose1 = new Mat();
            if ((int)text2.Sum() < text2.Rows * text2.Cols / 2)
            {
                //Mat seClose1 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
                seClose1 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(9, 1));
            }
            else
            {
                seClose1 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 1));
            }
            Mat close1 = new Mat();
            Cv2.MorphologyEx(threshEdge, close1, MorphTypes.Close, seClose1);

            //上方置零
            Cv2.Rectangle(close1, new Rect(0, 0, close1.Cols, BY[1] - 60), new Scalar(0), -1);
            //先将小点去掉
            Mat noMin = new Mat();
            GetArea(close1, out noMin, 10, true);
            //闭运算后得到最大连通域
            //如果边缘不明显
            Mat text = new Mat();
            switch (direction)
            {
                case "left":
                    text = noMin[B_Y[1] - 40, B_Y[1] - 10, B_X, BX];
                    break;
                case "right":
                    text = noMin[B_Y[1] - 40, B_Y[1] - 10, BX, B_X];
                    break;
            }

            Mat result = new Mat();
            Mat max = new Mat();
            if ((int)text.Sum() < (text.Rows * text.Cols) / 3)
            {
                result = noMin.Clone();
            }
            else if ((int)text.Sum() < (text.Rows * text.Cols) / 2)
            {
                Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
                Mat close = new Mat();
                Cv2.MorphologyEx(noMin, close, MorphTypes.Close, se);

                GetMaxArea(close, out max);
                result = max.Clone();
            }

            else
            {
                Cv2.Rectangle(noMin, new Rect(B_X - 20, B_Y[1] - 40, 10, 60), new Scalar(1), -1);
                GetMaxArea(noMin, out max);
                result = max.Clone();
            }
            #endregion

            //ImageShow(close1, noMin * 255, result * 255);
            //计算上纵坐标
            for (int i = B_Y[1] - 60; i < result.Rows; i++)
            {
                if (result.Get<byte>(i, B_X) > 0)
                {
                    B_Y[0] = i;
                    break;
                }
            }
            for (int i = BY[1] - 60; i < result.Rows; i++)
            {
                if (result.Get<byte>(i, BX) > 0)
                {
                    BY[0] = i;
                    break;
                }
            }

            int compensate = 5;
            BY[0] += compensate;
            B_Y[0] += compensate;
        }
        public void GaoduchaBOrdinateY3(Mat thresh, Mat image, out int[] BY, out int[] B_Y, int BX, int B_X, string direction)
        {
            BY = new int[2];
            B_Y = new int[2];
            #region//计算下纵坐标
            for (int i = 0; i < thresh.Rows; i++)
            {
                if (thresh.Get<byte>(i, B_X) > 0)
                {
                    B_Y[1] = i;
                    break;
                }
            }
            for (int i = 0; i < thresh.Rows; i++)
            {
                if (thresh.Get<byte>(i, BX) > 0)
                {
                    BY[1] = i;
                    break;
                }
            }
            #endregion
            #region//图像处理
            //阈值分割，保留最大连通域
            Mat crop = new Mat();
            switch (direction)
            {
                case "left":
                    crop = image[BY[1] - 60, BY[1] - 10, B_X - 10, BX + 10].Clone();
                    Cv2.Rectangle(image, new Rect(B_X - 10, BY[1] - 60, BX + 10 - (B_X - 10), 50), new Scalar(255), 2);
                    break;
                case "right":
                    crop = image[BY[1] - 60, BY[1] - 10, BX - 10, B_X + 10].Clone();
                    break;
            }
            Mat thresh2 = new Mat();
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\image.png", image * 1);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\crop.png", crop * 1);
            double t = Cv2.Threshold(crop, thresh2, 0, 1, ThresholdTypes.Otsu);
            Mat fanse = 1 - thresh2;
            Mat nomin = fanse.Clone();// new Mat();
            //GetMaxArea(fanse, out nomin);
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 1));
            Mat open = new Mat();
            Cv2.MorphologyEx(nomin, open, MorphTypes.Open, seOpen);
            //ImageShow(fanse * 255, nomin * 255, open * 255,crop+open*100);
            Mat result = new Mat();// open.Clone();//
            Fill(open, out result, 1);
            Cv2.ImWrite(@"C:\Users\54434\Desktop\result.png", result * 255);
            #endregion
            #region//计算上纵坐标
            int[] lower = new int[2];
            int[] upper = new int[2];
            int compensate = 7;
            Scalar sum = new Scalar(0);
            int upper_temp = 0;
            int upper_max = 0;
            switch (direction)
            {
                case "left":
                    //B*
                    for (int i = 0; i < result.Rows - 1; i++)
                    {
                        sum = result[i, i + 1, 0, 20].Sum();
                        if ((int)sum > 10)
                        {
                            if (upper_temp == 0)
                            {
                                if (upper[0] == 0 || upper_max < 13)
                                    upper_temp = i;
                                else if ((int)(result[i, i + 1, 0, result.Cols - 1].Sum()) > result.Cols - 20)
                                    upper_temp = i;
                            }
                            if ((int)sum > upper_max/*13*/)
                                upper_max = (int)sum;// break;//避免找到内部的干扰点
                        }
                        else if (upper_temp > 0)
                        {
                            upper[0] = upper_temp;
                            upper_temp = 0;
                        }
                    }
                    if (upper_temp > 0)
                    {
                        upper[0] = upper_temp;
                        upper_temp = 0;
                    }
                    upper_max = 0;
                    for (int i = result.Rows - 1; i > 1; i--)
                    {
                        sum = result[i - 1, i, 0, 20].Sum();
                        if ((int)sum > 10)
                        {
                            lower[0] = i;
                            break;
                        }
                    }
                    //B
                    for (int i = 0; i < result.Rows - 1; i++)
                    {
                        sum = result[i, i + 1, result.Cols - 20, result.Cols].Sum();
                        if ((int)sum > 10)
                        {
                            if (upper_temp == 0)
                            {
                                if(upper[1] == 0 || upper_max < 13)
                                    upper_temp = i;
                                else if ((int)(result[i, i + 1, 0, result.Cols - 1].Sum()) > result.Cols - 20)
                                    upper_temp = i;
                            }
                            if ((int)sum > upper_max/*13*/)
                                upper_max = (int)sum;// break;//避免找到内部的干扰点
                        }
                        else if (upper_temp > 0)
                        {
                            upper[1] = upper_temp;
                            upper_temp = 0;
                        }
                    }
                    if (upper_temp > 0)
                    {
                        upper[1] = upper_temp;
                        upper_temp = 0;
                    }
                    upper_max = 0;
                    for (int i = result.Rows - 1; i > 1; i--)
                    {
                        sum = result[i - 1, i, result.Cols - 20, result.Cols].Sum();
                        if ((int)sum > 10)
                        {
                            lower[1] = i;
                            break;
                        }
                    }
                    if (lower[0] - upper[0] > 10)
                    {
                        B_Y[0] = upper[0] + compensate + BY[1] - 60;
                    }
                    else
                    {
                        B_Y[0] = (upper[0] + lower[0]) / 2 + BY[1] - 60;
                    }
                    if (lower[1] - upper[1] > 10)
                    {
                        BY[0] = upper[1] + compensate + BY[1] - 60;
                    }
                    else
                    {
                        BY[0] = (upper[1] + lower[1]) / 2 + BY[1] - 60;
                    }
                    break;
                case "right":
                    //B
                    for (int i = 0; i < result.Rows - 1; i++)
                    {
                        sum = result[i, i + 1, 0, 20].Sum();
                        if ((int)sum >= 10)
                        {
                            if (upper_temp == 0)
                            {
                                if (upper[0] == 0 || upper_max < 13)
                                    upper_temp = i;
                                else if ((int)(result[i, i + 1, 0, result.Cols - 1].Sum()) > result.Cols - 20
                                    || (int)(result[i, i + 1, 0, result.Cols - 1].Sum()) > result.Cols / 2)
                                    upper_temp = i;
                            }
                            if ((int)sum > upper_max/*13*/)
                                upper_max = (int)sum;// break;//避免找到内部的干扰点
                        }
                        else if (upper_temp > 0 && (int)sum < 7)
                        {
                            upper[0] = upper_temp;
                            upper_temp = 0;
                        }
                    }
                    if (upper_temp > 0)
                    {
                        upper[0] = upper_temp;
                        upper_temp = 0;
                    }
                    upper_max = 0;
                    for (int i = result.Rows - 1; i > 1; i--)
                    {
                        sum = result[i - 1, i, 0, 20].Sum();
                        if ((int)sum > 10)
                        {
                            lower[0] = i;
                            break;
                        }
                    }
                    //B*
                    for (int i = 0; i < result.Rows - 1; i++)
                    {
                        sum = result[i, i + 1, result.Cols - 20, result.Cols].Sum();
                        if ((int)sum > 10)
                        {
                            if (upper_temp == 0)
                            {
                                if (upper[1] == 0 || upper_max < 13)
                                    upper_temp = i;
                                else if ((int)(result[i, i + 1, 0, result.Cols - 1].Sum()) > result.Cols - 20
                                    || (int)(result[i, i + 1, 0, result.Cols - 1].Sum()) > result.Cols / 2)
                                    upper_temp = i;
                            }
                            if ((int)sum > upper_max/*13*/)
                                upper_max = (int)sum;// break;//避免找到内部的干扰点
                        }
                        else if (upper_temp > 0)
                        {
                            upper[1] = upper_temp;
                            upper_temp = 0;
                        }
                    }
                    if (upper_temp > 0)
                    {
                        upper[1] = upper_temp;
                        upper_temp = 0;
                    }
                    upper_max = 0;
                    for (int i = result.Rows - 1; i > 1; i--)
                    {
                        sum = result[i - 1, i, result.Cols - 20, result.Cols].Sum();
                        if ((int)sum > 10)
                        {
                            lower[1] = i;
                            break;
                        }
                    }
                    if (lower[0] - upper[0] > 10)
                    {
                        BY[0] = upper[0] + compensate + BY[1] - 60;
                    }
                    else
                    {
                        BY[0] = (upper[0] + lower[0]) / 2 + BY[1] - 60;
                    }
                    if (lower[1] - upper[1] > 10)
                    {
                        B_Y[0] = upper[1] + compensate + BY[1] - 60;
                    }
                    else
                    {
                        B_Y[0] = (upper[1] + lower[1]) / 2 + BY[1] - 60;
                    }
                    break;
            }
            #endregion

        }
        /// <summary>
        /// 得到高度差全的提取区域
        /// </summary>
        /// <param name="imageGreen">绿色通道图</param>
        /// <param name="result">输出提取区域图</param>
        /// <param name="dataArea">提取区域</param>
        /// <param name="y">提取区域的上下界</param>
        public void GaoduchaQuanGetDataArea(Mat imageGreen, out Mat result, out int[] dataArea, out int[] y)
        {
            dataArea = new int[4];
            y = new int[2];
            Mat edge = new Mat();
            Sobel(imageGreen, out edge);
            Mat thresh = new Mat();
            thresh = edge.Threshold(0, 255, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Mat close = new Mat();
            Cv2.MorphologyEx(thresh, close, MorphTypes.Close, seClose);
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(1, 3));
            Mat open = new Mat();
            Cv2.MorphologyEx(close, open, MorphTypes.Open, seOpen);
            Mat seOpen2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Cv2.MorphologyEx(open, open, MorphTypes.Open, seOpen2);
            Mat fill = new Mat();
            Fill(open, out fill, 255);
            fill = fill / 255;
            Mat connect = fill.Clone();
            Scalar sum = new Scalar(0);
            int k = 0;
            bool flag = true;//真是找大于200的，假时找等于0 的
            int border = 0;
            while (k < connect.Cols - 1)
            {
                if (flag)
                {
                    for (k = border; k < fill.Cols; k++)
                    {
                        sum = fill[0, fill.Rows, k, k + 1].Sum();
                        if ((int)sum > 200)
                        {
                            Cv2.Rectangle(connect, new Rect(k, 0, 100, fill.Rows), new Scalar(1), -1);
                            border = k + 100;
                            flag = false;
                            break;
                        }
                    }
                }
                else
                {
                    for (k = border; k < fill.Cols; k++)
                    {
                        sum = fill[0, fill.Rows, k, k + 1].Sum();
                        if ((int)sum == 0)
                        {
                            border = k;
                            flag = true;
                            break;
                        }
                    }
                }
            }
            //Cv2.Rectangle(connect, new Rect(0, 0, fill.Cols, 1), new Scalar(1), -1);
            //Cv2.Rectangle(connect, new Rect(0, fill.Rows-1, fill.Cols, 1), new Scalar(1), -1);
            //保留前二大面积
            Mat[] contours;
            Mat hierachy = new Mat();
            Cv2.FindContours(connect, out contours, hierachy, RetrievalModes.External, ContourApproximationModes.ApproxNone);

            double largest = 0, secondLargest = 0;
            int index1 = 0, index2 = 0;
            for (int i = 0; i < contours.Count(); i++)
            {
                if (Cv2.ContourArea(contours[i]) > largest)
                {
                    largest = Cv2.ContourArea(contours[i]);
                    index1 = i;
                }
                else if (Cv2.ContourArea(contours[i]) > secondLargest)
                {
                    largest = Cv2.ContourArea(contours[i]);
                    index2 = i;
                }
            }

            result = Mat.Zeros(connect.Rows, connect.Cols, connect.Type());
            Cv2.DrawContours(result, contours, index1, new Scalar(1));
            Cv2.DrawContours(result, contours, index2, new Scalar(1));
            Mat fill2 = new Mat();
            Fill(result, out fill2, 1);
            Cv2.BitwiseAnd(fill, fill2, result);

            for (int i = 0; i < result.Rows; i++)
            {
                sum = result[i, i + 1, 0, result.Cols].Sum();
                if ((int)sum > 20)
                {
                    y[0] = i - 20;
                    break;
                }
            }
            for (int i = result.Rows - 1; i > 0; i--)
            {
                sum = result[i - 1, i, 0, result.Cols].Sum();
                if ((int)sum > 20)
                {
                    y[1] = i;
                    break;
                }
            }
            for (int j = 0; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum > 0)
                {
                    dataArea[0] = j;
                    break;
                }
            }
            for (int j = dataArea[0]; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum == 0)
                {
                    dataArea[1] = j;
                    break;
                }
            }
            for (int j = result.Cols - 1; j > 0; j--)
            {
                sum = result[y[0], y[1], j - 1, j].Sum();
                if ((int)sum > 0)
                {
                    dataArea[3] = j;
                    break;
                }
            }
            for (int j = dataArea[3]; j > 0; j--)
            {
                sum = result[y[0], y[1], j - 1, j].Sum();
                if ((int)sum == 0)
                {
                    dataArea[2] = j;
                    break;
                }
            }
            //ImageShow(open, connect * 255, result * 255);
        }
        public void GaoduchaQuanGetDataArea2(Mat imageRed, out Mat result, out int[] dataArea, out int[] y)
        {
            //result = new Mat();
            dataArea = new int[4];
            y = new int[2];
            Mat thresh = new Mat();
            double t = Cv2.Threshold(imageRed, thresh, 0, 1, ThresholdTypes.Otsu);
            if (t > 170)
                thresh = imageRed.Threshold(t + 30, 1, ThresholdTypes.Binary);
            //Mat max = new Mat();
            //GetMaxArea(thresh, out max);
            //ImageShow(thresh * 255);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Mat close = new Mat();
            Cv2.MorphologyEx(thresh, close, MorphTypes.Close, seClose);
            Mat fill = new Mat();
            Fill(close, out fill, 255);
            Mat connect = fill.Clone();
            Scalar sum = new Scalar(0);
            int k = 0;
            bool flag = true;//真是找大于200的，假时找等于0 的
            int border = 0;
            while (k < connect.Cols - 1)
            {
                if (flag)
                {
                    for (k = border; k < thresh.Cols; k++)
                    {
                        sum = thresh[0, thresh.Rows, k, k + 1].Sum();
                        if ((int)sum > 200)
                        {
                            Cv2.Rectangle(connect, new Rect(k, 0, 100, thresh.Rows), new Scalar(1), -1);
                            border = k + 100;
                            flag = false;
                            break;
                        }
                    }
                }
                else
                {
                    for (k = border; k < thresh.Cols; k++)
                    {
                        sum = thresh[0, thresh.Rows, k, k + 1].Sum();
                        if ((int)sum == 0)
                        {
                            border = k;
                            flag = true;
                            break;
                        }
                    }
                }
            }
            //保留前二大面积
            Mat[] contours;
            Mat hierachy = new Mat();
            Cv2.FindContours(connect, out contours, hierachy, RetrievalModes.External, ContourApproximationModes.ApproxNone);

            double largest = 0, secondLargest = 0;
            int index1 = 0, index2 = 0;
            for (int i = 0; i < contours.Count(); i++)
            {
                if (Cv2.ContourArea(contours[i]) > largest)
                {
                    largest = Cv2.ContourArea(contours[i]);
                    index1 = i;
                }
                else if (Cv2.ContourArea(contours[i]) > secondLargest)
                {
                    secondLargest = Cv2.ContourArea(contours[i]);
                    index2 = i;
                }
            }

            result = Mat.Zeros(connect.Rows, connect.Cols, connect.Type());
            Cv2.DrawContours(result, contours, index1, new Scalar(1));
            Cv2.DrawContours(result, contours, index2, new Scalar(1));
            Mat fill2 = new Mat();
            Fill(result, out fill2, 1);
            Cv2.BitwiseAnd(fill, fill2, result);

            //ImageShow(connect * 255, result * 255);

            for (int i = 0; i < result.Rows; i++)
            {
                sum = result[i, i + 1, 0, result.Cols].Sum();
                if ((int)sum > 20)
                {
                    y[0] = i - 20;
                    break;
                }
            }
            for (int i = result.Rows - 1; i > 0; i--)
            {
                sum = result[i - 1, i, 0, result.Cols].Sum();
                if ((int)sum > 20)
                {
                    y[1] = i;
                    break;
                }
            }
            for (int j = 0; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum > 0)
                {
                    dataArea[0] = j;
                    break;
                }
            }
            for (int j = dataArea[0]; j < result.Cols; j++)
            {
                sum = result[y[0], y[1], j, j + 1].Sum();
                if ((int)sum == 0)
                {
                    dataArea[1] = j;
                    break;
                }
            }
            for (int j = result.Cols - 1; j > 0; j--)
            {
                sum = result[y[0], y[1], j - 1, j].Sum();
                if ((int)sum > 0)
                {
                    dataArea[3] = j;
                    break;
                }
            }
            for (int j = dataArea[3]; j > 0; j--)
            {
                sum = result[y[0], y[1], j - 1, j].Sum();
                if ((int)sum == 0)
                {
                    dataArea[2] = j;
                    break;
                }
            }

        }
        public void GaoduchaQuanGetDataArea3(Mat imageRed, Mat image, out int[] leftTonghou, out int[] rightTonghou, out int[] dataArea, out int[] y)
        {

            dataArea = new int[4];
            y = new int[2];
            leftTonghou = new int[3];
            rightTonghou = new int[3];
            Mat thresh = new Mat();
            double t = Cv2.Threshold(imageRed, thresh, 0, 1, ThresholdTypes.Otsu);
            if (t > 170)
                thresh = imageRed.Threshold(240, 1, ThresholdTypes.Binary);
            //ImageShow(thresh * 255);
            //当还是太亮时，需要判断，使用边缘检测加填充方法
            Mat maxArea = new Mat();
            GetMaxArea(thresh, out maxArea);
            bool flag = false;
            double maxAreaSum = (double)maxArea.Sum();
            if ((int)maxArea.Sum() > 350000)
            {
                Mat gray = new Mat();
                Cv2.CvtColor(image, gray, ColorConversionCodes.BGR2GRAY);
                thresh = gray.Threshold(200, 1, ThresholdTypes.Binary);
                //Mat edge = new Mat();
                //Sobel(imageRed, out edge);
                //Mat edgeThresh = new Mat();
                //edgeThresh = edge.Threshold(50, 1, ThresholdTypes.Binary);
                //Mat edgeMax = new Mat();
                //GetMaxArea(edgeThresh, out edgeMax);
                //flag = true;
                //ImageShow(edgeThresh * 255, edgeMax * 255);
            }
            //ImageShow(thresh * 255);
            Cv2.Rectangle(thresh, new Rect(thresh.Cols - 1, 0, 1, thresh.Rows), new Scalar(1), -1);//当右侧出现非整体铜体时连接
            Cv2.Rectangle(thresh, new Rect(0, 0, 1, thresh.Rows), new Scalar(1), -1);//也可能出现在左侧
            //闭运算
            Mat seClose = new Mat();
            if (t < 170)
                seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(9, 9));
            else
                seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Mat close = new Mat();
            Cv2.MorphologyEx(thresh, close, MorphTypes.Close, seClose);
            Fill(close, out close, 1);
            //ImageShow(close * 255);
            //保留前二大区域
            Mat hierachy = new Mat();
            Mat[] contoursMat;
            Cv2.FindContours(close, out contoursMat, hierachy, RetrievalModes.External, ContourApproximationModes.ApproxNone);
            double max1 = 0, max2 = 0;
            int idx1 = 0, idx2 = 0;
            for (int i = 0; i < contoursMat.Count(); i++)
            {
                if (Cv2.ContourArea(contoursMat[i]) > max1)
                {
                    max2 = max1;
                    idx2 = idx1;
                    max1 = Cv2.ContourArea(contoursMat[i]);
                    idx1 = i;
                }
                else if (Cv2.ContourArea(contoursMat[i]) > max2)
                {
                    max2 = Cv2.ContourArea(contoursMat[i]);
                    idx2 = i;
                }
            }
            Mat qianerArea = new Mat(thresh.Size(), thresh.Type());
            Cv2.DrawContours(qianerArea, contoursMat, idx1, new Scalar(1));
            Cv2.DrawContours(qianerArea, contoursMat, idx2, new Scalar(1));
            Fill(qianerArea, out qianerArea, 1);
            thresh = qianerArea;
            Cv2.Rectangle(thresh, new Rect(thresh.Cols - 1, 0, 1, thresh.Rows), new Scalar(0), -1);//将连接线去掉
            Cv2.Rectangle(thresh, new Rect(0, 0, 1, thresh.Rows), new Scalar(0), -1);//
            //
            int middle = imageRed.Cols / 2;
            //ImageShow(thresh * 255);
            Scalar sum = new Scalar(0);
            Scalar max = new Scalar(0);
            //左右列像素最多的地方,并且提取目标区域
            int leftBorde = 0, rightBorder = 0;
            for (int j = 0; j < middle; j++)
            {
                sum = thresh[0, thresh.Rows, j, j + 1].Sum();
                if ((int)sum > (int)max)
                {
                    max = sum;
                    leftBorde = j;
                    dataArea[0] = leftBorde;
                }
            }
            max = 0;
            for (int j = thresh.Cols - 1; j > middle; j--)
            {
                sum = thresh[0, thresh.Rows, j - 1, j].Sum();
                if ((int)sum > (int)max)
                {
                    max = sum;
                    rightBorder = j;
                    dataArea[3] = rightBorder;
                }
            }

            //目标区域的上下界
            for (int i = 0; i < thresh.Rows; i++)
            {
                sum = thresh[i, i + 1, 0, thresh.Cols].Sum();
                if ((int)sum > 0)
                {
                    y[0] = i;
                    break;
                }
            }
            for (int i = thresh.Rows - 1; i > 0; i--)
            {
                sum = thresh[i - 1, i, 0, thresh.Cols].Sum();
                if ((int)sum > 0)
                {
                    y[1] = i;
                    break;
                }
            }
            //目标区域中间
            if (flag == false)
            {
                //Cv2.ImWrite(@"C:\Users\54434\Desktop\thresh.png", thresh * 120);
                for (int j = leftBorde; j < thresh.Cols; j++)
                {
                    sum = thresh[y[0], y[1], j, j + 1].Sum();
                    if ((int)sum == 0)
                    {
                        dataArea[1] = j;
                        break;
                    }
                }
                for (int j = rightBorder - 1; j > middle; j--)
                {
                    sum = thresh[y[0], y[1], j - 1, j].Sum();
                    if ((int)sum == 0)
                    {
                        dataArea[2] = j;
                        break;
                    }
                }
            }
            //else
            //{
            //    Scalar lastSum = new Scalar(0);
            //    for (int j = middle; j > 100; j-=5)
            //    {
            //        sum = thresh[y[0], y[1], j - 3, j].Sum();
            //        if ((int)sum - (int)lastSum > 100&& lastSum!=0)
            //        {
            //            dataArea[1] = j;
            //            break;
            //        }
            //        lastSum = sum;
            //    }
            //    lastSum = 0;
            //    for (int j = middle; j <thresh.Cols-100; j+=5)
            //    {
            //        sum = thresh[y[0], y[1], j , j+5].Sum();
            //        if ((int)sum - (int)lastSum > 150 && lastSum != 0)
            //        {
            //            dataArea[2] = j;
            //            break;
            //        }
            //        lastSum = sum;
            //    }
            //}
            //边缘检测并横向腐蚀，去掉小连通域，提取铜厚
            Mat sobel = new Mat();
            Sobel(thresh, out sobel);
            Mat result = sobel.Clone();
            //Mat sobel = new Mat();
            //Cv2.GaussianBlur(imageRed, imageRed, new Size(11, 11), 5, 5);
            //Cv2.MedianBlur(imageRed, imageRed, 5);
            //Sobel(imageRed, out sobel);
            //Mat sobelThresh = new Mat();
            //double t2 = Cv2.Threshold(sobel, sobelThresh, 0, 255, ThresholdTypes.Otsu);
            //sobelThresh = sobel.Threshold(5, 255, ThresholdTypes.Binary);
            //Mat seErode = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(30, 1));
            //Mat erode = new Mat();
            //Cv2.Erode(sobelThresh, erode, seErode);
            //Mat noMinArea = new Mat();
            //GetArea(erode, out noMinArea, 500, true);
            //Mat result = noMinArea.Clone();
            //ImageShow(result * 255);
            leftTonghou[0] = dataArea[0] + 100;
            rightTonghou[0] = dataArea[3] - 100;
            //计算线纵坐标
            //左
            for (int i = y[0]; i < y[1]; i++)
            {
                if (result.Get<byte>(i, leftTonghou[0]) > 0)
                {
                    leftTonghou[1] = i;
                    break;
                }
            }
            for (int i = leftTonghou[1] + 60; i < y[1]; i++)
            {
                if (result.Get<byte>(i, leftTonghou[0]) > 0)
                {
                    leftTonghou[2] = i;
                    break;
                }
            }
            for (int i = leftTonghou[2]; i < y[1]; i++)
            {
                if (result.Get<byte>(i, leftTonghou[0]) == 0)
                {
                    leftTonghou[2] = i;
                    break;
                }
            }
            //右
            for (int i = y[0]; i < y[1]; i++)
            {
                if (result.Get<byte>(i, rightTonghou[0]) > 0)
                {
                    rightTonghou[1] = i;
                    break;
                }
            }
            for (int i = rightTonghou[1] + 60; i < y[1]; i++)
            {
                if (result.Get<byte>(i, rightTonghou[0]) > 0)
                {
                    rightTonghou[2] = i;
                    break;
                }
            }
            for (int i = rightTonghou[2]; i < y[1]; i++)
            {
                if (result.Get<byte>(i, rightTonghou[0]) == 0)
                {
                    rightTonghou[2] = i;
                    break;
                }
            }

            if (/*leftTonghou[2] - rightTonghou[2] > 400 && rightTonghou[2] * 3 > result.Rows
                || */leftTonghou[2] - rightTonghou[2] > 300 && rightTonghou[2] * 3 > result.Rows)
            {
                if (leftTonghou[2] - rightTonghou[2] > 400 && rightTonghou[2] * 3 > result.Rows)
                    leftTonghou[0] = leftTonghou[0] + 400;
                else if (leftTonghou[2] - rightTonghou[2] > 300 && rightTonghou[2] * 3 > result.Rows)
                    leftTonghou[0] = leftTonghou[0] + 430;
                //计算线纵坐标
                //左
                for (int i = y[0]; i < y[1]; i++)
                {
                    if (result.Get<byte>(i, leftTonghou[0]) > 0)
                    {
                        leftTonghou[1] = i;
                        break;
                    }
                }
                for (int i = leftTonghou[1] + 60; i < y[1]; i++)
                {
                    if (result.Get<byte>(i, leftTonghou[0]) > 0)
                    {
                        leftTonghou[2] = i;
                        break;
                    }
                }
                for (int i = leftTonghou[2]; i < y[1]; i++)
                {
                    if (result.Get<byte>(i, leftTonghou[0]) == 0)
                    {
                        leftTonghou[2] = i;
                        break;
                    }
                }
            }
            if (leftTonghou[2] - rightTonghou[2] > 400 && rightTonghou[2] * 3 < result.Rows
                || rightTonghou[2] - leftTonghou[2] > 300 && leftTonghou[2] * 3 > result.Rows)
            {
                if (leftTonghou[2] - rightTonghou[2] > 400 && rightTonghou[2] * 3 < result.Rows)
                    rightTonghou[0] = rightTonghou[0] - 400;
                else if (rightTonghou[2] - leftTonghou[2] > 300 && leftTonghou[2] * 3 > result.Rows)
                    rightTonghou[0] = rightTonghou[0] - 550;
                //右
                for (int i = y[0]; i < y[1]; i++)
                {
                    if (result.Get<byte>(i, rightTonghou[0]) > 0)
                    {
                        rightTonghou[1] = i;
                        break;
                    }
                }
                for (int i = rightTonghou[1] + 60; i < y[1]; i++)
                {
                    if (result.Get<byte>(i, rightTonghou[0]) > 0)
                    {
                        rightTonghou[2] = i;
                        break;
                    }
                }
                for (int i = rightTonghou[2]; i < y[1]; i++)
                {
                    if (result.Get<byte>(i, rightTonghou[0]) == 0)
                    {
                        rightTonghou[2] = i;
                        break;
                    }
                }
                if (rightTonghou[2] - leftTonghou[2] > 300 && leftTonghou[2] * 3 > result.Rows)
                    rightTonghou[2] = leftTonghou[2];
            }
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\result.png", result * 120);
            ////ExtractLines(thresh,out left1,leftBorde+200)
            ////ImageShow(sobelThresh,erode,maxArea*255);
        }

        public void GaoduchaQuanGetDataArea3_Center(Mat imageRed, Mat image, out int[] leftTonghou, out int[] rightTonghou, out int[] dataArea, out int[] y, int[] dataArea0)
        {

            dataArea = new int[4];
            y = new int[2];
            leftTonghou = new int[3];
            rightTonghou = new int[3];
            Mat thresh = new Mat();
            double t = Cv2.Threshold(imageRed, thresh, 0, 1, ThresholdTypes.Otsu);
            if (t > 170)
                thresh = imageRed.Threshold(240, 1, ThresholdTypes.Binary);
            //ImageShow(thresh * 255);
            //当还是太亮时，需要判断，使用边缘检测加填充方法
            Mat maxArea = new Mat();
            GetMaxArea(thresh, out maxArea);
            bool flag = false;
            double maxAreaSum = (double)maxArea.Sum();
            if ((int)maxArea.Sum() > 350000)
            {
                Mat gray = new Mat();
                Cv2.CvtColor(image, gray, ColorConversionCodes.BGR2GRAY);
                thresh = gray.Threshold(200, 1, ThresholdTypes.Binary);
                //Mat edge = new Mat();
                //Sobel(imageRed, out edge);
                //Mat edgeThresh = new Mat();
                //edgeThresh = edge.Threshold(50, 1, ThresholdTypes.Binary);
                //Mat edgeMax = new Mat();
                //GetMaxArea(edgeThresh, out edgeMax);
                //flag = true;
                //ImageShow(edgeThresh * 255, edgeMax * 255);
            }
            //ImageShow(thresh * 255);
            Cv2.Rectangle(thresh, new Rect(thresh.Cols - 1, 0, 1, thresh.Rows), new Scalar(1), -1);//当右侧出现非整体铜体时连接
            Cv2.Rectangle(thresh, new Rect(0, 0, 1, thresh.Rows), new Scalar(1), -1);//也可能出现在左侧
            //闭运算
            Mat seClose = new Mat();
            if (t < 170)
                seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(9, 9));
            else
                seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Mat close = new Mat();
            Cv2.MorphologyEx(thresh, close, MorphTypes.Close, seClose);
            Fill(close, out close, 1);
            //ImageShow(close * 255);
            //保留前二大区域
            Mat hierachy = new Mat();
            Mat[] contoursMat;
            Cv2.FindContours(close, out contoursMat, hierachy, RetrievalModes.External, ContourApproximationModes.ApproxNone);
            double max1 = 0, max2 = 0;
            int idx1 = 0, idx2 = 0;
            for (int i = 0; i < contoursMat.Count(); i++)
            {
                if (Cv2.ContourArea(contoursMat[i]) > max1)
                {
                    max2 = max1;
                    idx2 = idx1;
                    max1 = Cv2.ContourArea(contoursMat[i]);
                    idx1 = i;
                }
                else if (Cv2.ContourArea(contoursMat[i]) > max2)
                {
                    max2 = Cv2.ContourArea(contoursMat[i]);
                    idx2 = i;
                }
            }
            Mat qianerArea = new Mat(thresh.Size(), thresh.Type());
            Cv2.DrawContours(qianerArea, contoursMat, idx1, new Scalar(1));
            Cv2.DrawContours(qianerArea, contoursMat, idx2, new Scalar(1));
            Fill(qianerArea, out qianerArea, 1);
            thresh = qianerArea;
            Cv2.Rectangle(thresh, new Rect(thresh.Cols - 1, 0, 1, thresh.Rows), new Scalar(0), -1);//将连接线去掉
            Cv2.Rectangle(thresh, new Rect(0, 0, 1, thresh.Rows), new Scalar(0), -1);//
            //
            int middle = imageRed.Cols / 2;
            //ImageShow(thresh * 255);
            Scalar sum = new Scalar(0);
            Scalar max = new Scalar(0);
            //左右列像素最多的地方,并且提取目标区域
            int leftBorde = 0, rightBorder = 0;
            for (int j = 0; j < middle; j++)
            {
                sum = thresh[0, thresh.Rows, j, j + 1].Sum();
                if ((int)sum > (int)max)
                {
                    max = sum;
                    leftBorde = dataArea0[0];// j;
                    dataArea[0] = dataArea0[0];// leftBorde;
                }
            }
            max = 0;
            for (int j = thresh.Cols - 1; j > middle; j--)
            {
                sum = thresh[0, thresh.Rows, j - 1, j].Sum();
                if ((int)sum > (int)max)
                {
                    max = sum;
                    rightBorder = dataArea0[3];// j;
                    dataArea[3] = dataArea0[3];// rightBorder;
                }
            }

            //目标区域的上下界
            for (int i = 0; i < thresh.Rows; i++)
            {
                sum = thresh[i, i + 1, 0, thresh.Cols].Sum();
                if ((int)sum > 0)
                {
                    y[0] = i;
                    break;
                }
            }
            for (int i = thresh.Rows - 1; i > 0; i--)
            {
                sum = thresh[i - 1, i, 0, thresh.Cols].Sum();
                if ((int)sum > 0)
                {
                    y[1] = i;
                    break;
                }
            }
            //目标区域中间
            if (flag == false)
            {
                for (int j = leftBorde; j < thresh.Cols; j++)
                {
                    sum = thresh[y[0], y[1], j, j + 1].Sum();
                    if ((int)sum == 0)
                    {
                        dataArea[1] = j - 120;
                        break;
                    }
                }
                for (int j = rightBorder - 100; j > middle; j--)
                {
                    sum = thresh[y[0], y[1], j - 1, j].Sum();
                    if ((int)sum == 0)
                    {
                        dataArea[2] = j - 120;
                        break;
                    }
                }
            }
            //else
            //{
            //    Scalar lastSum = new Scalar(0);
            //    for (int j = middle; j > 100; j-=5)
            //    {
            //        sum = thresh[y[0], y[1], j - 3, j].Sum();
            //        if ((int)sum - (int)lastSum > 100&& lastSum!=0)
            //        {
            //            dataArea[1] = j;
            //            break;
            //        }
            //        lastSum = sum;
            //    }
            //    lastSum = 0;
            //    for (int j = middle; j <thresh.Cols-100; j+=5)
            //    {
            //        sum = thresh[y[0], y[1], j , j+5].Sum();
            //        if ((int)sum - (int)lastSum > 150 && lastSum != 0)
            //        {
            //            dataArea[2] = j;
            //            break;
            //        }
            //        lastSum = sum;
            //    }
            //}
            //边缘检测并横向腐蚀，去掉小连通域，提取铜厚
            Mat sobel = new Mat();
            Sobel(thresh, out sobel);
            Mat result = sobel.Clone();
            //Mat sobel = new Mat();
            //Cv2.GaussianBlur(imageRed, imageRed, new Size(11, 11), 5, 5);
            //Cv2.MedianBlur(imageRed, imageRed, 5);
            //Sobel(imageRed, out sobel);
            //Mat sobelThresh = new Mat();
            //double t2 = Cv2.Threshold(sobel, sobelThresh, 0, 255, ThresholdTypes.Otsu);
            //sobelThresh = sobel.Threshold(5, 255, ThresholdTypes.Binary);
            //Mat seErode = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(30, 1));
            //Mat erode = new Mat();
            //Cv2.Erode(sobelThresh, erode, seErode);
            //Mat noMinArea = new Mat();
            //GetArea(erode, out noMinArea, 500, true);
            //Mat result = noMinArea.Clone();
            //ImageShow(result * 255);
            leftTonghou[0] = dataArea[0] + 100;
            rightTonghou[0] = dataArea[3] - 100;
            //计算线纵坐标
            //左
            for (int i = y[0]; i < y[1]; i++)
            {
                if (result.Get<byte>(i, leftTonghou[0]) > 0)
                {
                    leftTonghou[1] = i;
                    break;
                }
            }
            for (int i = leftTonghou[1] + 60; i < y[1]; i++)
            {
                if (result.Get<byte>(i, leftTonghou[0]) > 0)
                {
                    leftTonghou[2] = i;
                    break;
                }
            }
            for (int i = leftTonghou[2]; i < y[1]; i++)
            {
                if (result.Get<byte>(i, leftTonghou[0]) == 0)
                {
                    leftTonghou[2] = i;
                    break;
                }
            }
            //右
            for (int i = y[0]; i < y[1]; i++)
            {
                if (result.Get<byte>(i, rightTonghou[0]) > 0)
                {
                    rightTonghou[1] = i;
                    break;
                }
            }
            for (int i = rightTonghou[1] + 60; i < y[1]; i++)
            {
                if (result.Get<byte>(i, rightTonghou[0]) > 0)
                {
                    rightTonghou[2] = i;
                    break;
                }
            }
            for (int i = rightTonghou[2]; i < y[1]; i++)
            {
                if (result.Get<byte>(i, rightTonghou[0]) == 0)
                {
                    rightTonghou[2] = i;
                    break;
                }
            }

            if (/*leftTonghou[2] - rightTonghou[2] > 400 && rightTonghou[2] * 3 > result.Rows
                || */leftTonghou[2] - rightTonghou[2] > 300 && rightTonghou[2] * 3 > result.Rows)
            {
                if (leftTonghou[2] - rightTonghou[2] > 400 && rightTonghou[2] * 3 > result.Rows)
                    leftTonghou[0] = leftTonghou[0] + 400;
                else if (leftTonghou[2] - rightTonghou[2] > 300 && rightTonghou[2] * 3 > result.Rows)
                    leftTonghou[0] = leftTonghou[0] + 430;
                //计算线纵坐标
                //左
                for (int i = y[0]; i < y[1]; i++)
                {
                    if (result.Get<byte>(i, leftTonghou[0]) > 0)
                    {
                        leftTonghou[1] = i;
                        break;
                    }
                }
                for (int i = leftTonghou[1] + 60; i < y[1]; i++)
                {
                    if (result.Get<byte>(i, leftTonghou[0]) > 0)
                    {
                        leftTonghou[2] = i;
                        break;
                    }
                }
                for (int i = leftTonghou[2]; i < y[1]; i++)
                {
                    if (result.Get<byte>(i, leftTonghou[0]) == 0)
                    {
                        leftTonghou[2] = i;
                        break;
                    }
                }
            }
            if (leftTonghou[2] - rightTonghou[2] > 400 && rightTonghou[2] * 3 < result.Rows
                || rightTonghou[2] - leftTonghou[2] > 300 && leftTonghou[2] * 3 > result.Rows)
            {
                if (leftTonghou[2] - rightTonghou[2] > 400 && rightTonghou[2] * 3 < result.Rows)
                    rightTonghou[0] = rightTonghou[0] - 400;
                else if (rightTonghou[2] - leftTonghou[2] > 300 && leftTonghou[2] * 3 > result.Rows)
                    rightTonghou[0] = rightTonghou[0] - 550;
                //右
                for (int i = y[0]; i < y[1]; i++)
                {
                    if (result.Get<byte>(i, rightTonghou[0]) > 0)
                    {
                        rightTonghou[1] = i;
                        break;
                    }
                }
                for (int i = rightTonghou[1] + 60; i < y[1]; i++)
                {
                    if (result.Get<byte>(i, rightTonghou[0]) > 0)
                    {
                        rightTonghou[2] = i;
                        break;
                    }
                }
                for (int i = rightTonghou[2]; i < y[1]; i++)
                {
                    if (result.Get<byte>(i, rightTonghou[0]) == 0)
                    {
                        rightTonghou[2] = i;
                        break;
                    }
                }
                if (rightTonghou[2] - leftTonghou[2] > 300 && leftTonghou[2] * 3 > result.Rows)
                    rightTonghou[2] = leftTonghou[2];
            }
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\result.png", result * 120);
            ////ExtractLines(thresh,out left1,leftBorde+200)
            ////ImageShow(sobelThresh,erode,maxArea*255);
        }

        /// <summary>
        /// 计算高度差全的铜厚
        /// </summary>
        /// <param name="contour">二值图</param>
        /// <param name="leftTonghou">左侧铜厚，0：横坐标；1：上纵坐标；2：下纵坐标</param>
        /// <param name="rightTonghou">右侧铜厚，0：横坐标；1：上纵坐标；2：下纵坐标</param>
        /// <param name="dataArea">提取区域</param>
        /// <param name="y">目标区域上下边界</param>
        public void GaoduchaTonghou(Mat contour, out int[] leftTonghou, out int[] rightTonghou, int[] dataArea, int[] y)
        {
            leftTonghou = new int[3];
            rightTonghou = new int[3];
            leftTonghou[0] = dataArea[0] + 200;
            rightTonghou[0] = dataArea[3] - 200;
            Mat crop = contour[y[0], y[1], 0, contour.Cols].Clone();
            double leftOrdinate1 = 0;
            ExtractLines(crop, out leftOrdinate1, leftTonghou[0] - 5, leftTonghou[0] + 5, 1);
            double leftOrdinate2 = 0;
            ExtractLines(crop, out leftOrdinate2, leftTonghou[0] - 5, leftTonghou[0] + 5, leftOrdinate1, -1);
            double rightOrdinate1 = 0;
            ExtractLines(crop, out rightOrdinate1, rightTonghou[0] - 5, rightTonghou[0] + 5, 1);
            double rightOrdinate2 = 0;
            ExtractLines(crop, out rightOrdinate2, rightTonghou[0] - 5, rightTonghou[0] + 5, rightOrdinate1, -1);
            leftTonghou[1] = (int)leftOrdinate1 + y[0];
            leftTonghou[2] = (int)leftOrdinate2 + y[0];
            rightTonghou[1] = (int)rightOrdinate1 + y[0];
            rightTonghou[2] = (int)rightOrdinate2 + y[0];
        }
        /// <summary>
        /// 计算高度差全的防焊厚度
        /// </summary>
        /// <param name="imageGreen">绿色通道图</param>
        /// <param name="leftFanghanhou">左侧防焊厚度，0：横坐标；1：上纵坐标；2：下纵坐标</param>
        /// <param name="rightFanghanhou">右侧防焊厚度，0：横坐标；1：上纵坐标；2：下纵坐标</param>
        /// <param name="dataArea">提取区域</param>
        /// <param name="tonghou">其中一个铜厚坐标</param>
        public void GaoduchaFanhanhou(Mat imageGreen, out int[] leftFanghanhou, out int[] rightFanghanhou, int[] dataArea, int[] tonghou)
        {
            leftFanghanhou = new int[3];
            rightFanghanhou = new int[3];
            int range = 30;
            int range2 = 80;
            //将目标区域选出来
            PointEnhancement(imageGreen, out imageGreen);
            Cv2.GaussianBlur(imageGreen, imageGreen, new Size(5, 5), 3, 3);
            Mat crop = imageGreen[tonghou[1] - range, tonghou[2] + range, dataArea[1] + range2, dataArea[2] - range2].Clone();

            Mat contour = new Mat();
            double t = Cv2.Threshold(crop, contour, 0, 1, ThresholdTypes.Otsu);
            contour = 255 - crop.Threshold(t - 5, 255, ThresholdTypes.Binary);

            Mat edge = new Mat();
            Sobel(crop, out edge);

            Mat thresh = edge.Threshold(0, 255, ThresholdTypes.Otsu);
            //新增
            Mat maxArea1 = new Mat();
            GetMaxArea(contour, out maxArea1);
            maxArea1 = maxArea1 * 255;

            Mat and = new Mat();
            Cv2.BitwiseAnd(thresh, maxArea1, and);
            //ImageShow(contour, thresh,and);

            //Mat delete = new Mat();
            //GetArea(thresh, out delete, 10,true);
            //delete = delete * 255;

            //
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 2));
            Mat close = new Mat();
            Cv2.MorphologyEx(thresh, close, MorphTypes.Close, seClose);

            Mat fill = new Mat();
            Fill(close, out fill, 255);
            //ImageShow(thresh, close, fill);
            Mat maxArea = new Mat();
            GetMaxArea(fill, out maxArea);
            Mat seClose2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(9, 3));
            Cv2.MorphologyEx(maxArea, close, MorphTypes.Close, seClose2);
            Fill(close, out fill, 255);
            Mat result = fill.Clone() / 255;
            //得到提取点
            Scalar sum = new Scalar(0);
            for (int j = 0; j < result.Cols; j++)
            {
                sum = result[0, result.Rows, j, j + 40].Sum();
                if ((int)sum > 2800)
                {
                    leftFanghanhou[0] = j + 100;
                    break;
                }
            }
            for (int j = result.Cols - 1; j > 0; j--)
            {
                sum = result[0, result.Rows, j - 40, j].Sum();
                if ((int)sum > 2800)
                {
                    rightFanghanhou[0] = j - 100;
                    break;
                }
            }
            //计算高度
            double leftOrdinate1 = 0;
            ExtractLines(and, out leftOrdinate1, leftFanghanhou[0] - 5, leftFanghanhou[0] + 5, 1);
            double leftOrdinate2 = 0;
            and = and / 255;
            for (int i = and.Rows - 1; i > and.Rows / 2; i--)
            {
                sum = and[i - 1, i, 0, leftFanghanhou[0]].Sum();
                if ((int)sum > 5)
                {
                    leftOrdinate2 = i;
                    break;
                }
            }
            //ExtractLines(result, out leftOrdinate2, leftFanghanhou[0] - 5, leftFanghanhou[0] + 5,leftOrdinate1, -1);
            //ExtractLines2(and, out leftOrdinate2, 5, 15,  1);
            double rightOrdinate1 = 0;
            ExtractLines(and, out rightOrdinate1, rightFanghanhou[0] - 5, rightFanghanhou[0] + 5, 1);
            double rightOrdinate2 = 0;
            for (int i = and.Rows - 1; i > and.Rows / 2; i--)
            {
                sum = and[i - 1, i, rightFanghanhou[0], and.Cols].Sum();
                if ((int)sum > 5)
                {
                    rightOrdinate2 = i;
                    break;
                }
            }
            //ExtractLines(result, out rightOrdinate2, rightFanghanhou[0] - 5, rightFanghanhou[0] + 5, rightOrdinate1, -1);
            //ExtractLines2(and, out rightOrdinate2, and.Cols-15, and.Cols- 5, 1);
            leftFanghanhou[0] += dataArea[1] + range2;
            leftFanghanhou[1] = (int)leftOrdinate1 + tonghou[1] - range;
            leftFanghanhou[2] = (int)leftOrdinate2 + tonghou[1] - range;
            rightFanghanhou[0] += dataArea[1] + range2;
            rightFanghanhou[1] = (int)rightOrdinate1 + tonghou[1] - range;
            rightFanghanhou[2] = (int)rightOrdinate2 + tonghou[1] - range;
            //ImageShow(close*255, fill, maxArea * 255);
            //ImageShow(result * 255);
        }
        public void GaoduchaFanhanhou2(Mat imageRed, out int[] leftFanghanhou, out int[] rightFanghanhou, int[] dataArea, int[] tonghou)
        {
            leftFanghanhou = new int[3];
            rightFanghanhou = new int[3];
            int range = 30;
            int range2 = 80;
            //将目标区域选出来
            PointEnhancement(imageRed, out imageRed);
            Cv2.GaussianBlur(imageRed, imageRed, new Size(9, 9), 3, 3);
            Mat crop = imageRed[tonghou[1] - range, tonghou[2] + range, dataArea[1] + range2, dataArea[2] - range2].Clone();
            Mat sobel = new Mat();
            Sobel(crop, out sobel);
            Mat thresh = new Mat();
            double t = Cv2.Threshold(sobel, thresh, 0, 255, ThresholdTypes.Otsu);
            thresh = sobel.Threshold(5, 255, ThresholdTypes.Binary);

            Mat tangle = new Mat();
            Cv2.Rectangle(thresh, new Rect(0, 0, 10, thresh.Rows), new Scalar(255), -1);
            Cv2.Rectangle(thresh, new Rect(thresh.Cols - 11, 0, 10, thresh.Rows), new Scalar(255), -1);
            //清楚小点
            Mat noMin = new Mat();
            GetArea(thresh, out noMin, 10, true);
            //闭运算
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 1));
            Mat close = new Mat();
            Cv2.MorphologyEx(noMin, close, MorphTypes.Close, seClose);

            Mat max = new Mat();
            GetMaxArea(close, out max);
            //再次闭运算全连接
            Mat seClsoe2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(9, 3));
            Mat close2 = new Mat();
            Cv2.MorphologyEx(max, close2, MorphTypes.Close, seClsoe2);
            //ImageShow( thresh,noMin*255,max*255,close2*255);
            Mat result = close2.Clone();
            //得到提取点
            Scalar sum = new Scalar(0);
            for (int j = 20; j < result.Cols; j++)
            {
                sum = result[0, result.Rows, j, j + 40].Sum();
                if ((int)sum > 2800)
                {
                    leftFanghanhou[0] = j + 100;
                    break;
                }
            }
            for (int j = result.Cols - 21; j > 0; j--)
            {
                sum = result[0, result.Rows, j - 40, j].Sum();
                if ((int)sum > 2800)
                {
                    rightFanghanhou[0] = j - 100;
                    break;
                }
            }
            //计算高度
            for (int i = 0; i < result.Rows; i++)
            {
                sum = result[i, i + 1, leftFanghanhou[0] - 5, leftFanghanhou[0] + 5].Sum();
                if ((int)sum > 5)
                {
                    leftFanghanhou[1] = i;
                    break;
                }
            }
            for (int i = result.Rows - 1; i > 0; i--)
            {
                sum = result[i - 1, i, leftFanghanhou[0] - 5, leftFanghanhou[0] + 5].Sum();
                if ((int)sum > 5)
                {
                    leftFanghanhou[2] = i;
                    break;
                }
            }
            for (int i = 0; i < result.Rows; i++)
            {
                sum = result[i, i + 1, rightFanghanhou[0] - 5, rightFanghanhou[0] + 5].Sum();
                if ((int)sum > 5)
                {
                    rightFanghanhou[1] = i;
                    break;
                }
            }
            for (int i = result.Rows - 1; i > 0; i--)
            {
                sum = result[i - 1, i, rightFanghanhou[0] - 5, rightFanghanhou[0] + 5].Sum();
                if ((int)sum > 5)
                {
                    rightFanghanhou[2] = i;
                    break;
                }
            }
            int compensate = 13;
            leftFanghanhou[0] += dataArea[1] + range2;
            leftFanghanhou[1] += tonghou[1] - range;
            leftFanghanhou[2] += tonghou[1] - range - compensate;
            rightFanghanhou[0] += dataArea[1] + range2;
            rightFanghanhou[1] += tonghou[1] - range;
            rightFanghanhou[2] += tonghou[1] - range - compensate;
        }
        public void GaoduchaFanghanhoudu3(Mat image, out int[] leftFanghanhoudu, out int[] rightFanghanhoudu, int[] dataArea, int[] tonghou)
        {
            leftFanghanhoudu = new int[3];
            rightFanghanhoudu = new int[3];

            Mat gray = new Mat();
            Cv2.CvtColor(image, gray, ColorConversionCodes.BGR2GRAY);
            Cv2.GaussianBlur(gray, gray, new Size(9, 9), 3, 3);
            //Cv2.MedianBlur(gray, gray, 5);
            Mat sobel = new Mat();
            //Sobel(gray, out sobel);
            EdgeY(gray, out sobel);
            Mat sobelThresh = new Mat();
            double t = Cv2.Threshold(sobel, sobelThresh, 0, 255, ThresholdTypes.Otsu);
            sobelThresh = sobel.Threshold(10, 255, ThresholdTypes.Binary);
            //Mat seClsoe = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 1));
            //Mat close = new Mat();
            //Cv2.MorphologyEx(sobelThresh, close, MorphTypes.Close, seClsoe);
            Mat seErode = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 1));
            Mat erode = new Mat();
            Cv2.Erode(sobelThresh, erode, seErode);
            Mat crop = erode[tonghou[1] - 60, tonghou[2] + 40, dataArea[1], dataArea[2]].Clone();
            Mat noMinArea = new Mat();
            GetArea(crop, out noMinArea, 50, true);
            Mat result = new Mat();
            RemoveCircles(noMinArea, out result);
            Scalar sum = new Scalar(0);
            int startBorder = 0;
            for (int i = 10; i < result.Rows - 2; i++)
            {
                sum = result[i, i + 2, 0, result.Cols].Sum();
                if ((int)sum > 600)
                {
                    startBorder = i;
                    break;
                }
            }
            Cv2.Rectangle(result, new Rect(0, 0, result.Cols, startBorder), new Scalar(0), -1);
            GetArea(result, out result, 2000, true);
            //ImageShow(result * 255);
            int middle = crop.Cols / 2;



            leftFanghanhoudu[0] = middle - 150;
            rightFanghanhoudu[0] = middle + 150;
            double left1 = 0, left2 = 0;
            double right1 = 0, right2 = 0;
            ExtractLines(result, out left1, leftFanghanhoudu[0] - 10, leftFanghanhoudu[0] + 10, 1);
            ExtractLines(result, out right1, rightFanghanhoudu[0] - 10, rightFanghanhoudu[0] + 10, 1);
            //计算防焊下坐标
            Mat edgeLower = new Mat();
            Sobel(gray, out edgeLower);
            Mat edgeLowerThresh = edgeLower.Threshold(5, 1, ThresholdTypes.Binary);
            //ImageShow(edgeLowerThresh * 255);
            Mat crop2 = edgeLowerThresh[tonghou[2] - 20, tonghou[2] + 40, dataArea[1], dataArea[2]].Clone();
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 1));
            Mat close2 = new Mat();
            Cv2.MorphologyEx(crop2, close2, MorphTypes.Close, seOpen);
            Mat open = new Mat();
            Cv2.MorphologyEx(close2, open, MorphTypes.Open, seOpen);
            Mat bigArea = new Mat();
            //GetMaxArea(open, out bigArea);
            GetArea(open, out bigArea, 500, true);
            //ImageShow(bigArea * 255);
            //Mat cannyEdge = new Mat();
            //Cv2.Canny(gray, cannyEdge, 18, 14);
            //ImageShow(cannyEdge);
            int bigAreaSum = (int)bigArea.Sum();
            if (bigAreaSum < 5000)
                bigArea = result[result.Rows - 60, result.Rows, 0, result.Cols].Clone();
            ExtractLines2(bigArea, out left2, leftFanghanhoudu[0] - 10, leftFanghanhoudu[0] + 10, 1);
            ExtractLines2(bigArea, out right2, rightFanghanhoudu[0] - 10, rightFanghanhoudu[0] + 10, 1);

            int compensate1 = 10;
            int compensate2 = 0;
            leftFanghanhoudu[0] += dataArea[1];
            leftFanghanhoudu[1] = (int)left1 + tonghou[1] - 60 + compensate1;
            leftFanghanhoudu[2] = (int)left2 + tonghou[2] - 20 - compensate2;
            rightFanghanhoudu[0] += dataArea[1];
            rightFanghanhoudu[1] = (int)right1 + tonghou[1] - 60 + compensate1;
            rightFanghanhoudu[2] = (int)right2 + tonghou[2] - 20 - compensate2;
            //ImageShow(sobelThresh, crop, result * 255);
        }
        public void GaoduchaFanghanhoudu4(Mat image_0, out int[] leftFanghanhoudu, out int[] rightFanghanhoudu, int[] dataArea, int[] tonghou)
        {
            leftFanghanhoudu = new int[3];
            rightFanghanhoudu = new int[3];

            //防焊厚上层
            Mat gray = new Mat();
            Cv2.CvtColor(image_0, gray, ColorConversionCodes.BGR2GRAY);
            //Mat filter = new Mat();
            //PointEnhancement(gray, out filter);
            Mat newGray = gray.Clone();// new Mat();//
            //Cv2.GaussianBlur(gray, newGray, new Size(11, 11), 3, 3);
            Mat blur = new Mat();
            Cv2.MedianBlur(newGray, blur, 5);
            Mat edge;
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\blur.png", blur);
            EdgeY(blur, out edge);
            //Edge(blur, out edge);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\edge.png", edge);
            int meanV = (int)(edge[tonghou[1] - 30, tonghou[2], dataArea[1], dataArea[2]].Mean().Val0);
            if (meanV > 50) meanV -= 25;
            else if (meanV > 18)
            {
                if ((int)(edge[tonghou[1], tonghou[1] / 2 - 15 + tonghou[2] / 2, dataArea[1], dataArea[2]].Mean().Val0) * 2 < meanV)
                    meanV = (int)(edge[tonghou[1], tonghou[1] / 2 - 15 + tonghou[2] / 2, dataArea[1], dataArea[2]].Mean().Val0) / 2;
                else if (meanV > 20)
                    meanV /= 2;
                else
                    meanV -= 5;
            }
            //meanV = 2;// (int)(edge[tonghou[1], tonghou[1] / 2 - 15 + tonghou[2] / 2, dataArea[1], dataArea[2]].Mean().Val0)/2;// 2;// (int)(edge[tonghou[1], tonghou[1] / 2 - 15 + tonghou[2] / 2, dataArea[1], dataArea[2]].Mean().Val0);
            meanV = meanV < 13 ? meanV * 2 : meanV;
            Mat thresh = edge.Threshold(meanV/*15*/, 255, ThresholdTypes.Binary);

            Mat thresh2 = thresh.Clone();
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\thresh2_0.png", thresh2);
            Cv2.Rectangle(thresh2, new Rect(0, 0, thresh.Cols, tonghou[1] - 30), new Scalar(0), -1);
            Cv2.Rectangle(thresh2, new Rect(0, tonghou[2] + 20, thresh.Cols, thresh.Rows - tonghou[2] - 20), new Scalar(0), -1);
            Cv2.Rectangle(thresh2, new Rect(0, tonghou[1] + 40, thresh.Cols, tonghou[2] - tonghou[1]), new Scalar(255), -1);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\thresh2.png", thresh2);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            //Mat close = new Mat();
            //Cv2.MorphologyEx(thresh2, close, MorphTypes.Close, seClose);
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Mat open = new Mat();
            Cv2.MorphologyEx(thresh2, open, MorphTypes.Open, seOpen);
            Mat max = new Mat();
            //GetMaxArea(thresh2, out max);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\open.png", open);
            //GetMaxArea(open, out max/*thresh, out maxThresh*/);
            GetArea(open, out max, 500, true);
            //ImageShow(thresh, thresh2,open, max * 255);
            Mat result = max.Clone();
            int middle = (dataArea[1] + dataArea[2]) / 2;
            leftFanghanhoudu[0] = middle - 120;// 150;
            rightFanghanhoudu[0] = middle + 120;// 150;

            Mat seOpen11 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(70/*15*/, 1/*水平线<--3, 3*/));// 开运算
            //Mat open11 = new Mat();
            ////OpenCV提取图像中的垂直线（或者水平线） 定义结构元素，开操作
            Cv2.MorphologyEx(result, result, MorphTypes.Open, seOpen11);


            //Cv2.ImWrite(@"C:\Users\54434\Desktop\result.png", result * 120);
            //if (result.Get<byte>(tonghou[2] - 10, leftFanghanhoudu[0]) > 0)
            //{
            //    for (int i = tonghou[2] - 10; i > tonghou[1] - 30; i--)
            //    {
            //        if (result.Get<byte>(i, leftFanghanhoudu[0]) == 0)
            //        {
            //            leftFanghanhoudu[1] = i;
            //            break;
            //        }
            //    }
            //}
            //else
            {
                for (int i = tonghou[1] - 30; i < tonghou[2]; i++)
                {
                    if (result/*result*/.Get<byte>(i, leftFanghanhoudu[0]) > 0)
                    {
                        leftFanghanhoudu[1] = i;
                        if (max[i - 1, i, leftFanghanhoudu[0], rightFanghanhoudu[0]].Sum().Val0 >
                            (rightFanghanhoudu[0] - leftFanghanhoudu[0]) / 2 + 15
                            || Cv2.FloodFill(max, new Point(leftFanghanhoudu[0], i), new Scalar(1/*255*/)) > 3500)
                            break;//对弧形的判定！
                    }
                }
            }
            int upperLine = leftFanghanhoudu[1];
            for (int i = leftFanghanhoudu[1]; i > leftFanghanhoudu[1] - 5; i--)
            {
                if (max.Get<byte>(i, leftFanghanhoudu[0]) > 0)
                    upperLine = i;
                else break;
            }
            leftFanghanhoudu[1] = upperLine;

            //if (result.Get<byte>(tonghou[2] - 10, rightFanghanhoudu[0]) > 0)
            //{
            //    for (int i = tonghou[2] - 10; i > tonghou[1] - 30; i--)
            //    {
            //        if (result.Get<byte>(i, rightFanghanhoudu[0]) == 0)
            //        {
            //            rightFanghanhoudu[1] = i;
            //            break;
            //        }
            //    }
            //}
            //else
            {
                for (int i = tonghou[1] - 30; i < tonghou[2]; i++)
                {
                    if (result/*result*/.Get<byte>(i, rightFanghanhoudu[0]) > 0)
                    {
                        rightFanghanhoudu[1] = i;
                        if (max[i - 1, i, leftFanghanhoudu[0], rightFanghanhoudu[0]].Sum().Val0 >
                            (rightFanghanhoudu[0] - leftFanghanhoudu[0]) / 2 + 15
                            || Cv2.FloodFill(max, new Point(rightFanghanhoudu[0], i), new Scalar(1/*255*/)) > 3500)
                            break;//对弧形的判定！
                    }
                }
            }
            upperLine = rightFanghanhoudu[1];
            for (int i = rightFanghanhoudu[1]; i > rightFanghanhoudu[1] - 5; i--)
            {
                if (max.Get<byte>(i, rightFanghanhoudu[0]) > 0)
                    upperLine = i;
                else break;
            }
            rightFanghanhoudu[1] = upperLine;

            Scalar color = new Scalar(255/*2*//*127*//*255*/);
            //颜色
            Cv2.Line(gray, new Point(leftFanghanhoudu[0], leftFanghanhoudu[1]), new Point(leftFanghanhoudu[0], leftFanghanhoudu[2]), color, 2, LineTypes.Link8);
            Cv2.Line(gray, new Point(rightFanghanhoudu[0], rightFanghanhoudu[1]), new Point(rightFanghanhoudu[0], rightFanghanhoudu[2]), color, 2, LineTypes.Link8);
            Rect rectMin = new Rect(Math.Max(0, leftFanghanhoudu[0] - 130), Math.Max(0, leftFanghanhoudu[1] - 200),
                Math.Min(max.Cols-1, rightFanghanhoudu[0]+130)- Math.Max(0, leftFanghanhoudu[0] - 130),
                Math.Min(max.Rows-1, leftFanghanhoudu[1]+30)- Math.Max(0, leftFanghanhoudu[1] - 200));
            Cv2.Rectangle(gray, rectMin, color, 1);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray.png", gray/*max * 127*//*1*//*120*/);


            int[] compensate1 = new int[] { 10, 10 };
            //去掉球 以及 微调补偿数值
            Mat roundTemp = image_0[Math.Max(0, leftFanghanhoudu[1] - 200), Math.Min(max.Rows - 1, leftFanghanhoudu[1] + 30), 
                Math.Max(0, leftFanghanhoudu[0] - 130), Math.Min(max.Cols - 1, rightFanghanhoudu[0] + 130)].CvtColor(ColorConversionCodes.BGR2GRAY);
            //meanV = (int)(roundTemp.Mean().Val0);
            //Mat mat_er = roundTemp.Threshold(meanV/*15*/, 255, ThresholdTypes.Binary);

            CircleSegment[] circles = Cv2.HoughCircles(roundTemp, HoughMethods.Gradient, 1, 30, 70, 30, 10, 60/*60*/);//, dp, minDist, param1, param2, minRadius, maxRadius);
                                                                                                                                                      //CircleSegment[] circleSegment;
                                                                                                                                                      //Base.AutoMeasure.Ceju.RemoveCircles(image1, image2, out result, 1, 30, 70, 30, 10, 60);
            if (circles.Length > 0)
            {
                int range = 10;// 5;// 10;
                for (int ic = 0; ic < circles.Length; ic++)
                {
                    Point center = (Point)circles[ic].Center;
                    int radius = (int)circles[ic].Radius;
                    //for(int j=1;j<radius;j++)
                    //Cv2.Circle(result, center, j, new Scalar(1));    
                    Cv2.Rectangle(roundTemp, new Rect(center.X - radius - range, center.Y - radius - range, 2 * (radius + range), 2 * (radius + range)), new Scalar(255/*1*/), /*-*/1);

                    Cv2.Rectangle(max, new Rect(Math.Max(0, leftFanghanhoudu[0] - 130) + center.X - radius - range, Math.Max(0, leftFanghanhoudu[1] - 200) + center.Y - radius - range, 2 * (radius + range), 2 * (radius + range)), new Scalar(0), -1);
                }
            }
            else
            {
                Mat tempEr = roundTemp.Threshold(/*15*/(int)(roundTemp.Mean().Val0) - 5, 255, ThresholdTypes.BinaryInv);
                ////GetMaxArea(tempEr, out tempEr); tempEr = tempEr * 255;
                //Cv2.ImWrite(@"C:\Users\54434\Desktop\tempEr.png", tempEr/*max * 120*//*roundTemp*/);
                circles = Cv2.HoughCircles(tempEr, HoughMethods.Gradient, 1, 30, 70, 30, 10, 90/*60*/);//, dp, minDist, param1, param2, minRadius, maxRadius);
                                                                                                                                                                              //Base.AutoMeasure.Ceju.RemoveCircles(image1, image2, out result, 1, 30, 70, 30, 10, 60);
                if (circles.Length > 0)
                {
                    int range = 0;// 5;// 10;
                    for (int ic = 0; ic < circles.Length; ic++)
                    {
                        Point center = (Point)circles[ic].Center;
                        int radius = (int)circles[ic].Radius;
                        //for(int j=1;j<radius;j++)
                        //Cv2.Circle(result, center, j, new Scalar(1));    
                        Cv2.Rectangle(roundTemp, new Rect(center.X - radius - range, center.Y - radius - range, 2 * (radius + range), 2 * (radius + range)), new Scalar(255/*1*/), /*-*/1);

                        Cv2.Rectangle(max, new Rect(Math.Max(0, leftFanghanhoudu[0] - 130) + center.X - radius - range, Math.Max(0, leftFanghanhoudu[1] - 200) + center.Y - radius - range, 2 * (radius + range), 2 * (radius + range)), new Scalar(0), -1);
                    }
                }

            }
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray.png", roundTemp/*max * 120*//*roundTemp*/);

            //{
            //    for (int i = tonghou[1] - 30; i < tonghou[2]; i++)
            //    {
            //        if (result/*result*/.Get<byte>(i, leftFanghanhoudu[0]) > 0)
            //        {
            //            leftFanghanhoudu[1] = i;
            //            if (max[i - 1, i, leftFanghanhoudu[0], rightFanghanhoudu[0]].Sum().Val0 >
            //                (rightFanghanhoudu[0] - leftFanghanhoudu[0]) / 2 + 15
            //                || Cv2.FloodFill(max, new Point(leftFanghanhoudu[0], i), new Scalar(1/*255*/)) > 3500)
            //                break;//对弧形的判定！
            //        }
            //    }
            //}
            int comp = 5;
            if (rightFanghanhoudu[1] > leftFanghanhoudu[1] + 10)
                comp = 10;
            upperLine = leftFanghanhoudu[1] + comp;
            for (int i = leftFanghanhoudu[1]; i < leftFanghanhoudu[1] + comp; i++)
            {
                if (max.Get<byte>(i, leftFanghanhoudu[0]) > 0)
                {
                    upperLine = i;
                    break;
                }
            }
            leftFanghanhoudu[1] = upperLine;
            if (rightFanghanhoudu[1] < leftFanghanhoudu[1])
            {
                comp = 5;
                upperLine = rightFanghanhoudu[1] + 5;
                for (int i = rightFanghanhoudu[1]; i < rightFanghanhoudu[1] + 5; i++)
                {
                    if (max.Get<byte>(i, rightFanghanhoudu[0]) > 0)
                    {
                        upperLine = i;
                        break;
                    }
                }
                rightFanghanhoudu[1] = upperLine;
            }
            //{
            //    for (int i = tonghou[1] - 30; i < tonghou[2]; i++)
            //    {
            //        if (result/*result*/.Get<byte>(i, rightFanghanhoudu[0]) > 0)
            //        {
            //            rightFanghanhoudu[1] = i;
            //            if (max[i - 1, i, leftFanghanhoudu[0], rightFanghanhoudu[0]].Sum().Val0 >
            //                (rightFanghanhoudu[0] - leftFanghanhoudu[0]) / 2 + 15
            //                || Cv2.FloodFill(max, new Point(rightFanghanhoudu[0], i), new Scalar(1/*255*/)) > 3500)
            //                break;//对弧形的判定！
            //        }
            //    }
            //}


            ////Mat roundGray = new Mat();
            ////Cv2.CvtColor(roundTemp, roundGray, ColorConversionCodes.BGR2GRAY);
            ////int mean0; Scalar mean_rgb;
            //////去掉圆并灰度化，怎么能更快？
            ////Scalar mean = roundGray.Mean(/*gray*/);
            ////mean0 = (int)mean[0];
            ////mean_rgb = roundTemp/*srcImage*/.Mean();
            /////*final = */
            ////bool foundCircle;
            ////roundTemp = FangHanTools.RemoveCircle(roundTemp, mean0, mean_rgb, out foundCircle);//.CvtColor(ColorConversionCodes.BGR2GRAY);
            ///////*Mat roundTemp = */FangHanTools.RemoveCircle(roundTemp, out mean0, out roundTemp);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\gray.png", roundTemp/*max * 127*//*1*//*120*/);


            ////通过连接区域的大小判定是否在圆球范围内
            //int fillArea1 = 0;
            //for (int i = tonghou[1] - 30; i < tonghou[2]; i++)
            //{
            //    if (result.Get<byte>(i, leftFanghanhoudu[0]) > 0)
            //    {
            //        fillArea1 = Cv2.FloodFill(result.Clone()/*, mask1*/, new Point(leftFanghanhoudu[0], i), new Scalar(255/*127*//*255*/));
            //        leftFanghanhoudu[1] = i;
            //        break;
            //    }
            //}
            //Console.WriteLine("fillArea1:" + fillArea1);
            ////Cv2.ImWrite(@"C:\Users\54434\Desktop\result.png", result * 120);
            ////通过连接区域的大小判定是否在圆球范围内


            //int fillArea2 = 0;
            //for (int i = tonghou[1] - 30; i < tonghou[2]; i++)
            //{
            //    if (result.Get<byte>(i, rightFanghanhoudu[0]) > 0)
            //    {
            //        fillArea2 = Cv2.FloodFill(result.Clone()/*, mask1*/, new Point(rightFanghanhoudu[0], i), new Scalar(255/*127*//*255*/));
            //        rightFanghanhoudu[1] = i;
            //        break;
            //    }
            //}
            //Console.WriteLine("fillArea2:" + fillArea2);

            if (Math.Abs(leftFanghanhoudu[1] - rightFanghanhoudu[1]) > 100)
            {
                if (leftFanghanhoudu[1] < rightFanghanhoudu[1])
                    leftFanghanhoudu[1] = rightFanghanhoudu[1];
                else
                    rightFanghanhoudu[1] = leftFanghanhoudu[1];
            }
            //if (fillArea1 != fillArea2)
            //{
            //    if (leftFanghanhoudu[1] < rightFanghanhoudu[1])
            //        leftFanghanhoudu[1] = rightFanghanhoudu[1];
            //    else
            //        rightFanghanhoudu[1] = leftFanghanhoudu[1];
            //}


            //防焊厚下层
            Mat newGray2 = new Mat();
            Cv2.GaussianBlur(gray, newGray2, new Size(15, 15), 5, 5);
            Mat filter2 = new Mat();
            Cv2.MedianBlur(newGray2, filter2, 3);
            Mat edge2 = new Mat();
            Edge(filter2, out edge2);
            Mat thresh3 = new Mat();
            thresh3 = edge2.Threshold(15, 255, ThresholdTypes.Binary);
            Mat thresh4 = thresh3.Clone();
            Cv2.Rectangle(thresh4, new Rect(0, 0, thresh.Cols, tonghou[2] - 30), new Scalar(255), -1);
            Cv2.Rectangle(thresh4, new Rect(0, tonghou[2] + 40, thresh.Cols, thresh.Rows - tonghou[2] - 40), new Scalar(0), -1);
            Mat seOpen2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
            Mat open2 = new Mat();
            Cv2.MorphologyEx(thresh4, open2, MorphTypes.Open, seOpen2);
            Mat crop2 = open2[tonghou[2] - 20, tonghou[2] + 20, leftFanghanhoudu[0], rightFanghanhoudu[0]] / 255;
            int openSum = (int)crop2.Sum();
            int compensate2 = 8;
            if (openSum < 3000)
            {
                compensate2 = 0;
                Mat seClose2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 3));
                Cv2.MorphologyEx(thresh4, open2, MorphTypes.Close, seClose2);
            }
            Mat max2 = new Mat();
            GetMaxArea(thresh2, out max2);
            GetArea(open2, out max2, 500, true);
            //ImageShow(thresh3, thresh4, max2 * 255);
            //Cv2.ImWrite(@"C:\Users\54434\Desktop\max2.png", max2 * 255);
            Mat result2 = max2.Clone();

            //防焊厚上层
            Mat gray_1 = new Mat();
            Cv2.CvtColor(image_0, gray_1, ColorConversionCodes.BGR2GRAY);

            Scalar sum2 = new Scalar(0);
            for (int i = tonghou[2] + 20; i > tonghou[2] - 20; i--)
            {
                sum2 = result2[i - 1, i, leftFanghanhoudu[0] - 50, leftFanghanhoudu[0] + 50].Sum();
                if ((int)sum2 > 70)
                //if(result2.Get<byte>(i,leftFanghanhoudu[0])>0)
                {
                    leftFanghanhoudu[2] = i;
                    break;
                }
            }
            if (leftFanghanhoudu[2] == 0)
                leftFanghanhoudu[2] = tonghou[2];
            for (int i = tonghou[2] + 20; i > tonghou[2] - 20; i--)
            {
                sum2 = result2[i - 1, i, rightFanghanhoudu[0] - 50, rightFanghanhoudu[0] + 50].Sum();
                if ((int)sum2 > 70)
                //if(result2.Get<byte>(i, rightFanghanhoudu[0]) > 0)
                {
                    rightFanghanhoudu[2] = i;
                    break;
                }
            }
            if (rightFanghanhoudu[2] == 0)
                rightFanghanhoudu[2] = tonghou[2];
                //for (int i = tonghou[2] + 20; i > tonghou[2] - 20; i--)
                //{
                //    sum2 = result2[i - 1, i, rightFanghanhoudu[0] - 50, rightFanghanhoudu[0] + 50].Sum();
                //    if ((int)sum2 > 60)
                //    {
                //        rightFanghanhoudu[2] = i;
                //        break;
                //    }
                //}
            
            
            //int compensate1 = 10;

            leftFanghanhoudu[1] += compensate1[0];
            rightFanghanhoudu[1] += compensate1[1];


            int fanghanX1 = rightFanghanhoudu[0] - 15;// 10;// += 140;// 145;
            int fanghanX2 = rightFanghanhoudu[0] + 15;// 10;// -= 140;// 145;
            int leftY0 = leftFanghanhoudu[1];
            int rightY0 = rightFanghanhoudu[1];
            {
                int fanghanhouduY1 = leftFanghanhoudu[1];
                int minGray__2 = 255 * 300;// minGray;
                int fanghanTop = fanghanhouduY1 - 25;// 20;// 25;// 20;// 10;
                int fanghanhouduY_0 = fanghanhouduY1 + 60/*50*/ + 20;
                Mat grayRect = gray_1[fanghanTop, fanghanhouduY_0 - 20/*50*/, fanghanX1, fanghanX2];
                int fanghanhouduY1__2_bottom;

                fanghanhouduY1 -= fanghanTop;
                int fanghanhouduY1__2 = fanghanhouduY1;
                Gaoduchahoudu_ACC(grayRect, fanghanhouduY1 - 0/*19*//*15*//*5*//*(isLeft ? 8 : 1)*/, out fanghanhouduY1__2, out fanghanhouduY1__2_bottom, out minGray__2, 0);

                if (true && Math.Abs(fanghanhouduY1 - fanghanhouduY1__2) < 10/* <<15 16*//*11*//*<-10*//*20*//*10*/
                    || (fanghanhouduY1 - fanghanhouduY1__2 > 0 && fanghanhouduY1 - fanghanhouduY1__2 < 12/* <<15.12 <<10 *//*10*//*20*/))
                    //|| (!isLeft && Math.Abs(fanghanhouduY1 - fanghanhouduY1__2) < 25/*20*/))
                    fanghanhouduY1 = fanghanhouduY1__2/*fanghanhouduY1__2_bottom*//*fanghanhouduY1__2*/ + fanghanTop;// +5;
                else
                    fanghanhouduY1 = fanghanhouduY1 + fanghanTop;

                Console.WriteLine("leftFanghanhoudu[1]：" + leftFanghanhoudu[1] + ";fanghanhouduY1:" + fanghanhouduY1);
                leftFanghanhoudu[1] = fanghanhouduY1;
            }
            {
                int fanghanhouduY1 = rightFanghanhoudu[1];
                int minGray__2 = 255 * 300;// minGray;
                int fanghanTop = fanghanhouduY1 - 25;// 20;// 25;// 20;// 10;
                int fanghanhouduY_0 = fanghanhouduY1 + 60/*50*/ + 20;
                Mat grayRect = gray_1[fanghanTop, fanghanhouduY_0 - 20/*50*/, fanghanX1, fanghanX2];
                int fanghanhouduY1__2_bottom;

                fanghanhouduY1 -= fanghanTop;
                int fanghanhouduY1__2 = fanghanhouduY1;
                Gaoduchahoudu_ACC(grayRect, fanghanhouduY1 - 0/*19*//*15*//*5*//*(isLeft ? 8 : 1)*/, out fanghanhouduY1__2, out fanghanhouduY1__2_bottom, out minGray__2, 1);

                if (true && Math.Abs(fanghanhouduY1 - fanghanhouduY1__2) < 10/* <<15 16*//*11*//*<-10*//*20*//*10*/
                    || (fanghanhouduY1 - fanghanhouduY1__2 > 0 && fanghanhouduY1 - fanghanhouduY1__2 < 12/* <<15.12 <<10 *//*10*//*20*/))
                    //|| (!isLeft && Math.Abs(fanghanhouduY1 - fanghanhouduY1__2) < 25/*20*/))
                    fanghanhouduY1 = fanghanhouduY1__2/*fanghanhouduY1__2_bottom*//*fanghanhouduY1__2*/ + fanghanTop;// +5;
                else
                    fanghanhouduY1 = fanghanhouduY1 + fanghanTop;
                Console.WriteLine("rightFanghanhoudu[1]：" + rightFanghanhoudu[1] + ";fanghanhouduY1:" + fanghanhouduY1);
                rightFanghanhoudu[1] = fanghanhouduY1;
            }
            if (Math.Abs(leftFanghanhoudu[1] - rightFanghanhoudu[1]) - Math.Abs(leftY0 - rightY0) > 2)
            {//纠错2（1）.JPG
                if (leftY0 == leftFanghanhoudu[1])
                    rightFanghanhoudu[1] = rightY0;
                else if (rightY0 == rightFanghanhoudu[1])
                    if (Math.Abs(rightY0 - leftY0) > 10)
                    {
                        leftFanghanhoudu[1] = rightY0;// leftY0;
                    }
                    else
                        leftFanghanhoudu[1] = leftY0;
            }


            //Mat grayRect = gray_1[leftFanghanhoudu[1] - 10/*fanghanTop*/, leftFanghanhoudu[1] + 50/*fanghanhouduY_0 - 50*/, leftFanghanhoudu[0] - 10, leftFanghanhoudu[0] + 10];
            //Gaoduchahoudu_ACC(grayRect/*gray*/, y, marginTop/*150*//*fanghanhouduX*/, tonghouY, out fanghanhouduY1, out minGray);


            //int fanghanhouduY1__2 = fanghanhouduY1;
            //int minGray__2 = minGray;
            //fanghanX1 += 140;// 145;
            //fanghanX2 -= 140;// 145;
            //grayRect = gray[fanghanTop, fanghanhouduY_0 - 20/*50*/, fanghanX1, fanghanX2];

            //int fanghanhouduY1__2_bottom;
            //FanghanhouduForYouKaiKou_ACC(grayRect, y, marginTop, fanghanhouduY1 - (isLeft ? 8/*5*/ : 1), out fanghanhouduY1__2, out fanghanhouduY1__2_bottom, out minGray__2);

            //if (true && (Math.Abs(fanghanhouduY1 - fanghanhouduY1__2) < 16/*11*//*<-10*//*20*//*10*/
            //    || (!isLeft && Math.Abs(fanghanhouduY1 - fanghanhouduY1__2) < 25/*20*/)))
            //    fanghanhouduY1 = fanghanhouduY1__2/*fanghanhouduY1__2_bottom*//*fanghanhouduY1__2*/ + fanghanTop;// +5;
            //else
            //    fanghanhouduY1 = fanghanhouduY1 + fanghanTop;





            leftFanghanhoudu[2] -= compensate2;
            rightFanghanhoudu[2] -= compensate2;
        }

        /// <summary>
        /// 防焊 有开口 厚度 精确计算
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        /// <param name="tonghouY"></param>
        /// <param name="fanghanhouduY"></param>
        /// <param name="a"></param>
        private void Gaoduchahoudu_ACC(Mat gray0, int fanghanhouduY1__0, out int fanghanhouduY1, out int fanghanhouduY1Bottom, out int minGray, int a = 0)
        {
            int bottomYDistance = 15;// 30;
            int fanghanhouduY1__noSharp = -1;// fanghanhouduY1;
            {
                minGray = 300 * 255;
                int minRowIndex = 0; int colEnd = gray0.Cols - 1; int curGray; List<int> curGrayList = new List<int>();
                fanghanhouduY1Bottom = 0;
                for (int i = Math.Max(0, fanghanhouduY1__0 - 19/*1*//*5*//*10*/); i < Math.Min(fanghanhouduY1__0 + bottomYDistance/*25*/, gray0.Rows) - 5; i++)
                {
                    curGray = this.FanghanhouduForAreaMin(gray0, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                    curGrayList.Add(curGray);
                    if (curGray < minGray)
                    {
                        minRowIndex = i;
                        fanghanhouduY1Bottom = i;
                        minGray = curGray;
                    }
                }
                for (int i = minRowIndex - Math.Max(0, fanghanhouduY1__0 - 19/*1*//*5*//*10*/) + 2; i < curGrayList.Count; i += 2)
                {
                    if (Math.Abs(curGrayList[i] - minGray) < 10/*100*/)
                    {
                        minRowIndex += 1;
                        fanghanhouduY1Bottom += 2;
                    }
                    else
                        break;
                }
                fanghanhouduY1__noSharp = minRowIndex;// 84;// 72;// minRowIndex;
            }
            {
                minGray = 300 * 255;
                //锐化
                //Mat left_small_sharp = BinaryTools.BlurMaskFunction(left_small).CvtColor(ColorConversionCodes.BGRA2GRAY);
                Mat gray = BinaryTools.BlurMaskFunction(gray0.Clone()/*grayRect*/, 4f * 3.14f, 1, 10f).CvtColor(ColorConversionCodes.BGRA2GRAY);

                //Cv2.ImWrite(@"C:\Users\win10SSD\Desktop\BlurMask" + a + "_.jpg", gray);

                int minRowIndex = 0; int colEnd = gray.Cols - 1; int curGray; List<int> curGrayList = new List<int>();
                fanghanhouduY1Bottom = 0;
                for (int i = Math.Max(0, fanghanhouduY1__0 - 19/*1*//*5*//*10*/); i < Math.Min(fanghanhouduY1__0 + bottomYDistance/*25*/, gray.Rows) - 5; i++)
                {
                    curGray = this.FanghanhouduForAreaMin(gray, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                    curGrayList.Add(curGray);
                    if (curGray < minGray)
                    {
                        minRowIndex = i;
                        fanghanhouduY1Bottom = i;
                        minGray = curGray;
                    }
                }
                for (int i = minRowIndex - Math.Max(0, fanghanhouduY1__0 - 19/*1*//*5*//*10*/) + 2; i < curGrayList.Count; i += 2)
                {
                    if (Math.Abs(curGrayList[i] - minGray) < 10/*100*/)
                    {
                        minRowIndex += 1;
                        fanghanhouduY1Bottom += 2;
                    }
                    else
                        break;
                }
                //Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
                ////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
                fanghanhouduY1 = minRowIndex;// 84;// 72;// minRowIndex;
            }
            Console.Write("noSharp：" + fanghanhouduY1__noSharp + ";fanghanhouduY1:" + fanghanhouduY1 +"...");
            if (Math.Abs(fanghanhouduY1__noSharp - fanghanhouduY1) < 7/* <<7 8*//* << 6 *//*5*/
                || (fanghanhouduY1__noSharp - fanghanhouduY1 > 0 && fanghanhouduY1__noSharp - fanghanhouduY1 < 20))
            {
                fanghanhouduY1 = fanghanhouduY1__noSharp;
            }
            else
                Console.WriteLine("fanghanhouduY1 far away from fanghanhouduY1__noSharp.");
        }


        //叠构
        /// <summary>
        /// 得到叠构有导电布时铜层的数量以及当铜层大于二时的平均厚度
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="tongshu"></param>
        /// <param name="tonghou"></param>
        public void GetTongCengShuliang(Mat gray, out int tongshu, out int tonghou, out int jianhou)
        {
            tongshu = 0;
            tonghou = 0;
            jianhou = 0;
            Mat thresh = new Mat();
            thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            //ImageShow(thresh * 255);
            Mat nomin = new Mat();//去除小点防止干扰
            GetArea(thresh, out nomin, 500, true);
            Mat result = nomin.Clone();
            int[] y = new int[8];
            int middle = thresh.Cols / 2;//根据中间选取部分范围防止倾斜的干扰
            Scalar sum = new Scalar(0);
            for (int i = 0; i < thresh.Rows; i++)
            {
                sum = result[i, i + 1, middle - 100, middle + 100].Sum();
                if ((int)sum > 0)
                {
                    y[0] = i;
                    break;
                }
            }
            for (int i = y[0]; i < thresh.Rows; i++)
            {
                sum = result[i, i + 1, middle - 100, middle + 100].Sum();
                if ((int)sum == 0)
                {
                    y[1] = i;
                    break;
                }
            }
            for (int i = y[1]; i < thresh.Rows; i++)
            {
                sum = result[i, i + 1, middle - 100, middle + 100].Sum();
                if ((int)sum > 0)
                {
                    y[2] = i;
                    break;
                }
            }
            if (y[2] != 0)
            {
                for (int i = y[2]; i < thresh.Rows; i++)
                {
                    sum = result[i, i + 1, middle - 100, middle + 100].Sum();
                    if ((int)sum == 0)
                    {
                        y[3] = i;
                        break;
                    }
                }
                for (int i = y[3]; i < thresh.Rows; i++)
                {
                    sum = result[i, i + 1, middle - 100, middle + 100].Sum();
                    if ((int)sum > 0)
                    {
                        y[4] = i;
                        break;
                    }
                }
                if (y[4] != 0)
                {
                    for (int i = y[4]; i < thresh.Rows; i++)
                    {
                        sum = result[i, i + 1, middle - 100, middle + 100].Sum();
                        if ((int)sum == 0)
                        {
                            y[5] = i;
                            break;
                        }
                    }
                    for (int i = y[5]; i < thresh.Rows; i++)
                    {
                        sum = result[i, i + 1, middle - 100, middle + 100].Sum();
                        if ((int)sum > 0)
                        {
                            y[6] = i;
                            break;
                        }
                    }
                    if (y[6] != 0)
                    {
                        for (int i = y[6]; i < thresh.Rows; i++)
                        {
                            sum = result[i, i + 1, middle - 100, middle + 100].Sum();
                            if ((int)sum == 0)
                            {
                                y[7] = i;
                                break;
                            }
                        }
                    }
                }
            }
            if (y[2] == 0)
                tongshu = 1;
            else if (y[4] == 0)
                tongshu = 2;
            else if (y[6] == 0)
                tongshu = 3;
            else
                tongshu = 4;
            if (tongshu == 1)
            {
                tonghou = y[1] - y[0];
            }
            else if (tongshu == 2)
            {
                tonghou = (y[1] - y[0] + y[3] - y[2]) / 2;
                jianhou = y[2] - y[1];
            }
        }
        /// <summary>
        /// 提取有导电布时单层铜的坐标
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="ordinates"></param>
        public void DaoidanbuDanceng(Mat gray, out List<int> ordinates)
        {
            ordinates = new List<int>();

            //图片处理
            //无预处理图片边缘检测+阈值分割+去小面积用来提取导电布
            //高斯滤波+边缘检测+阈值分割+铜区域闭运算-反色-掩膜-+掩膜+去小面积提取中间线条

            //无预处理
            Mat sobel1 = new Mat();
            EdgeY2(gray, out sobel1);
            Mat threshSobel1 = new Mat();
            threshSobel1 = sobel1.Threshold(100, 1, ThresholdTypes.Binary);
            Mat nomin1 = new Mat();
            GetArea(threshSobel1, out nomin1, 500, true);
            Mat result1 = nomin1.Clone();
            //ImageShow(result1 * 255);

            //有预处理高斯滤波
            Mat filter = new Mat();
            Cv2.GaussianBlur(gray, filter, new Size(5, 5), 3);
            Mat sobel = new Mat();
            EdgeY2(filter, out sobel);
            Mat threshSobel = new Mat();
            threshSobel = sobel.Threshold(80, 1, ThresholdTypes.Binary);

            Mat thresh = new Mat();
            thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 7));
            Cv2.MorphologyEx(thresh, thresh, MorphTypes.Close, seClose);
            Mat fanse = 1 - thresh;

            Mat and = new Mat();
            Cv2.BitwiseAnd(fanse, threshSobel, and);

            Mat nomin = new Mat();
            GetArea(and, out nomin, 500, true);

            //ImageShow(threshSobel * 255, thresh * 255, and * 255,nomin*255);
            //提取坐标
            Mat result = nomin.Clone();
            int middle = result.Cols / 2;
            Scalar sum = new Scalar();
            for (int i = 0; i < result.Rows - 1; i++)
            {
                sum = result[i, i + 2, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Add(newOrdinate);
                    i += 30;
                }
            }
            if (ordinates[1] - ordinates[0] < 50)
                ordinates.RemoveAt(1);
            for (int i = ordinates[0] + 10; i < result.Rows; i++)
            {
                sum = result1[i, i + 1, middle - 10, middle + 10].Sum();
                if ((int)sum == 0)
                {
                    int newOrdinate = i;
                    ordinates.Insert(1, newOrdinate);
                    break;
                }
            }
            //if (ordinates[ordinates.Count - 1] - ordinates[ordinates.Count - 2] < 40)
            if (ordinates.Count == 7 || ordinates.Count == 9)
                ordinates.RemoveAt(ordinates.Count - 1);
            for (int i = ordinates[ordinates.Count - 1] + 10; i < result.Rows; i++)
            {
                sum = result1[i, i + 1, middle - 10, middle + 10].Sum();
                if ((int)sum == 0)
                {
                    int newOrdinate = i;
                    ordinates.Add(newOrdinate);
                    break;
                }
            }
        }
        /// <summary>
        /// 得到叠构的总厚
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="zonghou"></param>
        public void DiegouGetZonghou(Mat gray, out int zonghou)
        {
            zonghou = 0;
            Mat sobel = new Mat();
            EdgeY2(gray, out sobel);
            Mat thresh = sobel.Threshold(100, 1, ThresholdTypes.Binary);
            Mat nomin = new Mat();
            GetArea(thresh, out nomin, 500, true);
            Scalar sum = new Scalar();
            int[] y = new int[2];
            int middle = nomin.Cols / 2;
            for (int i = 0; i < thresh.Rows - 1; i++)
            {
                sum = nomin[i, i + 1, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    y[0] = i;
                    break;
                }
            }
            for (int i = thresh.Rows - 1; i > 1; i--)
            {
                sum = nomin[i - 1, i, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    y[1] = i;
                    break;
                }
            }
            zonghou = y[1] - y[0];
        }
        /// <summary>
        /// 无导电布单层时测总厚
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="zonghou"></param>
        public void DiegouGetZonghou2(Mat gray, out int zonghou)
        {
            zonghou = 0;
            Mat sobel = new Mat();
            EdgeY2(gray, out sobel);
            Mat thresh = sobel.Threshold(40, 1, ThresholdTypes.Binary);
            Mat nomin = new Mat();
            GetArea(thresh, out nomin, 500, true);
            //ImageShow(nomin * 255);
            Scalar sum = new Scalar();
            int[] y = new int[2];
            int middle = nomin.Cols / 2;
            for (int i = 0; i < thresh.Rows - 1; i++)
            {
                sum = nomin[i, i + 1, 0, nomin.Cols].Sum();
                if ((int)sum > 100)
                {
                    y[0] = i;
                    break;
                }
            }
            for (int i = thresh.Rows - 1; i > 1; i--)
            {
                sum = nomin[i - 1, i, 0, nomin.Cols].Sum();
                if ((int)sum > 100)
                {
                    y[1] = i;
                    break;
                }
            }
            zonghou = y[1] - y[0];
            if (zonghou > 600)//如果大于600，说明是亮图由于阈值太低而出现干扰，划到亮图里面去
            {
                zonghou = 200;
            }
        }
        /// <summary>
        /// 提取有导电布双层铜总厚大时的坐标
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="ordinates"></param>
        public void DaodianbuShuangcengZongHou(Mat gray, out List<int> ordinates)
        {
            ordinates = new List<int>();

            //图片处理
            //无预处理图片边缘检测+阈值分割+去小面积用来提取导电布
            //高斯滤波+边缘检测+阈值分割+铜区域闭运算-反色-掩膜-+掩膜+去小面积提取中间线条

            //无预处理
            Mat sobel1 = new Mat();
            EdgeY2(gray, out sobel1);
            Mat threshSobel1 = new Mat();
            threshSobel1 = sobel1.Threshold(100, 1, ThresholdTypes.Binary);
            Mat nomin1 = new Mat();
            GetArea(threshSobel1, out nomin1, 500, true);
            Mat result1 = nomin1.Clone();
            //ImageShow(result1 * 255);

            //有预处理高斯滤波
            Mat filter = new Mat();
            Cv2.GaussianBlur(gray, filter, new Size(5, 5), 3);
            Mat sobel = new Mat();
            EdgeY2(filter, out sobel);
            Mat threshSobel = new Mat();
            threshSobel = sobel.Threshold(100, 1, ThresholdTypes.Binary);

            Mat thresh = new Mat();
            thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 7));
            Cv2.MorphologyEx(thresh, thresh, MorphTypes.Close, seClose);
            Mat fanse = 1 - thresh;

            Mat and = new Mat();
            Cv2.BitwiseAnd(fanse, threshSobel, and);

            Mat nomin = new Mat();
            GetArea(and, out nomin, 500, true);

            //ImageShow(threshSobel * 255, thresh * 255, and * 255, nomin * 255+gray);
            //提取坐标
            Mat result = nomin.Clone();
            int middle = result.Cols / 2;
            Scalar sum = new Scalar();
            for (int i = 0; i < result.Rows - 1; i++)
            {
                sum = result[i, i + 2, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Add(newOrdinate);
                    i += 30;
                }
            }
            if (ordinates[5] - ordinates[4] < 50)
                ordinates.RemoveAt(5);
            for (int i = ordinates[4] + 10; i < result.Rows; i++)
            {
                sum = result1[i, i + 1, middle - 10, middle + 10].Sum();
                if ((int)sum == 0)
                {
                    int newOrdinate = i;
                    ordinates.Insert(5, newOrdinate);
                    break;
                }
            }
            if (ordinates[ordinates.Count - 1] - ordinates[ordinates.Count - 2] < 40)
                ordinates.RemoveAt(ordinates.Count - 1);
            for (int i = ordinates[ordinates.Count - 1] + 10; i < result.Rows; i++)
            {
                sum = result1[i, i + 1, middle - 10, middle + 10].Sum();
                if ((int)sum == 0)
                {
                    int newOrdinate = i;
                    ordinates.Add(newOrdinate);
                    break;
                }
            }
        }
        /// <summary>
        /// 提取有导电布时三层铜时的坐标
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="ordinates"></param>
        public void DaodianbuSanceng(Mat gray, out List<int> ordinates)
        {
            ordinates = new List<int>();

            //图片处理
            //无预处理图片边缘检测+阈值分割+去小面积用来提取导电布
            //高斯滤波+边缘检测+阈值分割+铜区域闭运算-反色-掩膜-+掩膜+去小面积提取中间线条

            //无预处理
            Mat sobel1 = new Mat();
            EdgeY2(gray, out sobel1);
            Mat threshSobel1 = new Mat();
            threshSobel1 = sobel1.Threshold(100, 1, ThresholdTypes.Binary);
            Mat nomin1 = new Mat();
            GetArea(threshSobel1, out nomin1, 500, true);
            Mat result1 = nomin1.Clone();
            //ImageShow(result1 * 255);

            //有预处理高斯滤波
            Mat filter = new Mat();
            Cv2.GaussianBlur(gray, filter, new Size(5, 5), 3);
            Mat sobel = new Mat();
            EdgeY2(filter, out sobel);
            Mat threshSobel = new Mat();
            threshSobel = sobel.Threshold(80, 1, ThresholdTypes.Binary);

            Mat thresh = new Mat();
            thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 7));
            Cv2.MorphologyEx(thresh, thresh, MorphTypes.Close, seClose);
            Mat fanse = 1 - thresh;

            Mat and = new Mat();
            Cv2.BitwiseAnd(fanse, threshSobel, and);

            Mat nomin = new Mat();
            GetArea(and, out nomin, 500, true);

            //ImageShow(threshSobel * 255, thresh * 255, and * 255, nomin * 255 + gray);
            //提取坐标
            Mat result = nomin.Clone();
            int middle = result.Cols / 2;
            Scalar sum = new Scalar();
            for (int i = 0; i < result.Rows - 1; i++)
            {
                sum = result[i, i + 2, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Add(newOrdinate);
                    i += 30;
                }
            }
            //第一层
            if (ordinates[1] - ordinates[0] < 50)
                ordinates.RemoveAt(1);
            for (int i = ordinates[0] + 10; i < result.Rows; i++)
            {
                sum = result1[i, i + 1, middle - 10, middle + 10].Sum();
                if ((int)sum == 0)
                {
                    int newOrdinate = i;
                    ordinates.Insert(1, newOrdinate);
                    break;
                }
            }
            //倒数第三层和倒数第四层，求倒数第四层
            if (ordinates[ordinates.Count - 3] - ordinates[ordinates.Count - 4] < 40)
                ordinates.RemoveAt(ordinates.Count - 3);
            for (int i = ordinates[ordinates.Count - 3] + 10; i < result.Rows; i++)
            {
                sum = result1[i, i + 1, middle - 10, middle + 10].Sum();
                if ((int)sum == 0)
                {
                    int newOrdinate = i;
                    ordinates.Insert(ordinates.Count - 2, newOrdinate);
                    break;
                }
            }
        }
        /// <summary>
        /// 提取无导电布时单层铜厚大时的坐标
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="ordinates"></param>
        public void WuDaodianbuDancengHou(Mat gray, out List<int> ordinates)
        {
            ordinates = new List<int>();
            //图像处理
            Mat filter = new Mat();
            Cv2.GaussianBlur(gray, filter, new Size(5, 5), 3);
            Mat sobel = new Mat();
            EdgeY2(filter, out sobel);
            Mat threshSobel = new Mat();
            threshSobel = sobel.Threshold(80, 1, ThresholdTypes.Binary);

            Mat thresh = new Mat();
            thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 7));
            Cv2.MorphologyEx(thresh, thresh, MorphTypes.Close, seClose);
            Mat fanse = 1 - thresh;

            Mat and = new Mat();
            Cv2.BitwiseAnd(fanse, threshSobel, and);

            Mat nomin = new Mat();
            GetArea(and, out nomin, 500, true);
            //ImageShow(threshSobel * 255, thresh * 255, and * 255, nomin * 255 + gray);
            //坐标提取
            Mat result = nomin.Clone();
            int middle = result.Cols / 2;
            Scalar sum = new Scalar();
            for (int i = 0; i < result.Rows - 1; i++)
            {
                sum = result[i, i + 2, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Add(newOrdinate);
                    i += 100;
                }
            }
        }
        /// <summary>
        /// 提取无导电布时，单层铜，总厚较窄时的坐标
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="ordinates"></param>
        public void WuDaodianbuDancengZhaiZonghouZhai(Mat gray, out List<int> ordinates)
        {
            ordinates = new List<int>();

            //图像处理
            Mat filter = new Mat();
            Cv2.GaussianBlur(gray, filter, new Size(5, 5), 3);
            Mat sobel = new Mat();
            EdgeY2(filter, out sobel);
            Mat threshSobel = new Mat();
            threshSobel = sobel.Threshold(60, 1, ThresholdTypes.Binary);

            Mat thresh = new Mat();
            thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 7));
            Cv2.MorphologyEx(thresh, thresh, MorphTypes.Close, seClose);
            Mat fanse = 1 - thresh;

            Mat and = new Mat();
            Cv2.BitwiseAnd(fanse, threshSobel, and);

            //Mat seClose2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 1));
            //Mat close2 = new Mat();
            //Cv2.MorphologyEx(and, close2, MorphTypes.Close, seClose2);
            Mat nomin = new Mat();
            GetArea(and, out nomin, 500, true);
            //ImageShow(threshSobel * 255, thresh * 255, and * 255, nomin * 255 + gray);
            //坐标提取
            Mat result = nomin.Clone();
            int middle = result.Cols / 2;
            Scalar sum = new Scalar();
            for (int i = 0; i < result.Rows - 1; i++)
            {
                sum = result[i, i + 2, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Add(newOrdinate);
                    i += 30;
                }
            }
            int compensate = 5;
            ordinates[ordinates.Count - 1] += compensate;
        }
        /// <summary>
        /// 提取无导电布时，单层铜，总厚较宽时的坐标
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="ordinates"></param>
        public void WuDaodianbuDancengZhaiZonghouKuan(Mat gray, out List<int> ordinates)
        {
            ordinates = new List<int>();

            //图像处理
            Mat filter = new Mat();
            Cv2.GaussianBlur(gray, filter, new Size(5, 5), 3);
            Mat sobel = new Mat();
            EdgeY2(filter, out sobel);
            Mat threshSobel = new Mat();
            threshSobel = sobel.Threshold(20, 1, ThresholdTypes.Binary);

            Mat thresh = new Mat();
            thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 7));
            Cv2.MorphologyEx(thresh, thresh, MorphTypes.Close, seClose);
            Mat fill = new Mat();
            Fill(thresh, out fill, 1);
            Mat fanse = 1 - fill;

            Mat and = new Mat();
            Cv2.BitwiseAnd(fanse, threshSobel, and);

            Mat seClose2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 1));
            Mat close2 = new Mat();
            Cv2.MorphologyEx(and, close2, MorphTypes.Close, seClose2);
            Mat nomin = new Mat();
            GetArea(close2, out nomin, 2000, true);
            //ImageShow(threshSobel * 255, thresh * 255, and * 255, nomin * 255 + gray);
            //坐标提取
            Mat result = nomin.Clone();
            int middle = result.Cols / 2;
            Scalar sum = new Scalar();
            int count = 0;
            for (int i = 0; i < result.Rows - 1; i++)
            {
                sum = result[i, i + 2, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Add(newOrdinate);
                    i += 30;
                    count++;
                }
                if (count == 3)
                    break;
            }
            //最后一行
            for (int i = result.Rows - 1; i > 2; i--)
            {
                sum = result[i - 1, i, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Add(newOrdinate);
                    break;
                }
            }
            for (int i = ordinates[ordinates.Count - 1] - 30; i > 2; i--)
            {
                sum = result[i - 2, i, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Insert(ordinates.Count - 1, newOrdinate);
                    break;
                }
            }

            int compensate = 5;
            ordinates[0] += compensate;
            //ordinates[ordinates.Count - 1] += compensate;
            //提取中间线
            Mat crop = gray[ordinates[0], ordinates[1], middle - 100, middle + 100].Clone();
            //Mat threshCrop = crop.Threshold(160, 1, ThresholdTypes.Binary);
            Mat cropSobel = new Mat();
            EdgeY2(crop, out cropSobel);
            Mat threshCropSobel = 1 - cropSobel.Threshold(40, 1, ThresholdTypes.Binary);
            Mat result2 = threshCropSobel.Clone();
            for (int i = 20; i < result2.Rows - 1; i++)
            {
                sum = result2[i, i + 2, 0, result2.Cols].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Insert(1, newOrdinate + ordinates[0] + 20);
                    break;
                }
            }
            //ImageShow(crop,  threshCropSobel * 255);
        }
        /// <summary>
        /// 提取无导电布双层铜层厚较大时
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="ordinates"></param>
        public void WuDaodianbuShuangcengCenghou(Mat gray, out List<int> ordinates)
        {
            ordinates = new List<int>();

            //图像处理
            Mat filter = new Mat();
            Cv2.GaussianBlur(gray, filter, new Size(9, 9), 3);
            Mat sobel = new Mat();
            EdgeY2(filter, out sobel);
            Mat threshSobel = new Mat();
            threshSobel = sobel.Threshold(80, 1, ThresholdTypes.Binary);

            Mat thresh = new Mat();
            thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 7));
            Cv2.MorphologyEx(thresh, thresh, MorphTypes.Close, seClose);
            Mat fill = new Mat();
            Fill(thresh, out fill, 1);
            Mat fanse = 1 - fill;

            Mat and = new Mat();
            Cv2.BitwiseAnd(fanse, threshSobel, and);

            //Mat seClose2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 1));
            //Mat close2 = new Mat();
            //Cv2.MorphologyEx(and, close2, MorphTypes.Close, seClose2);
            Mat nomin = new Mat();
            GetArea(and, out nomin, 2000, true);
            //ImageShow(threshSobel * 255, thresh * 255, and * 255, nomin * 255 + gray);
            //坐标提取
            Mat result = nomin.Clone();
            int middle = result.Cols / 2;
            Scalar sum = new Scalar();
            for (int i = 0; i < result.Rows - 1; i++)
            {
                sum = result[i, i + 2, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Add(newOrdinate + 5);
                    i += 100;
                }
            }
        }
        public void WudaodianbuShuangcengD(Mat gray, out List<int> ordinates)
        {
            ordinates = new List<int>();

            //图像处理
            Mat filter = new Mat();
            Cv2.GaussianBlur(gray, filter, new Size(9, 9), 3);
            Mat sobel = new Mat();
            EdgeY2(filter, out sobel);
            Mat threshSobel = new Mat();
            threshSobel = sobel.Threshold(40, 1, ThresholdTypes.Binary);

            Mat thresh = new Mat();
            thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 7));
            Cv2.MorphologyEx(thresh, thresh, MorphTypes.Close, seClose);
            Mat fill = new Mat();
            Fill(thresh, out fill, 1);
            Mat fanse = 1 - fill;

            Mat and = new Mat();
            Cv2.BitwiseAnd(fanse, threshSobel, and);

            Mat seClose2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 1));
            Mat close2 = new Mat();
            Cv2.MorphologyEx(and, close2, MorphTypes.Close, seClose2);

            Mat nomin = new Mat();
            GetArea(close2, out nomin, 3000, true);
            //Mat noCircle = new Mat();
            //RemoveCircles(nomin, out noCircle);
            //ImageShow(thresh * 255, and * 255,close2*255, nomin * 255 + gray);
            //坐标提取
            Mat result = nomin.Clone();
            int middle = result.Cols / 2;
            Scalar sum = new Scalar();
            for (int i = 0; i < result.Rows - 1; i++)
            {
                sum = result[i, i + 2, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Add(newOrdinate + 5);
                    i += 30;
                }
            }
            //迭代
            if (ordinates.Count < 11)
            {
                for (int i = 0; i < ordinates[0]; i++)
                {
                    sum = result[i, i + 2, 0, result.Cols].Sum();
                    if ((int)sum > 100)
                    {
                        int newOrdinate = i;
                        ordinates.Insert(0, newOrdinate + 5);
                        break;
                    }
                }
            }
            if (ordinates.Count == 12)
                ordinates.RemoveAt(11);
            if (ordinates.Count == 11)
            {
                ordinates[6] += 6;
                ordinates[8] += 6;
                ordinates[10] += 10;
            }
        }
        public void WudaodianbuShuangcengQita(Mat gray, out List<int> ordinates)
        {
            ordinates = new List<int>();

            //图像处理
            Mat filter = new Mat();
            Cv2.GaussianBlur(gray, filter, new Size(9, 9), 3);
            Mat sobel = new Mat();
            EdgeY2(filter, out sobel);
            Mat threshSobel = new Mat();
            threshSobel = sobel.Threshold(80, 1, ThresholdTypes.Binary);

            Mat thresh = new Mat();
            thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 7));
            Cv2.MorphologyEx(thresh, thresh, MorphTypes.Close, seClose);
            Mat fill = new Mat();
            Fill(thresh, out fill, 1);
            Mat fanse = 1 - fill;

            Mat and = new Mat();
            Cv2.BitwiseAnd(fanse, threshSobel, and);

            //Mat seClose2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 1));
            //Mat close2 = new Mat();
            //Cv2.MorphologyEx(and, close2, MorphTypes.Close, seClose2);
            Mat nomin = new Mat();
            GetArea(and, out nomin, 2000, true);
            //ImageShow(threshSobel * 255, thresh * 255, and * 255, nomin * 255 + gray);
            //坐标提取
            Mat result = nomin.Clone();
            int middle = result.Cols / 2;
            Scalar sum = new Scalar();
            for (int i = 0; i < result.Rows - 1; i++)
            {
                sum = result[i, i + 2, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Add(newOrdinate + 5);
                    i += 30;
                }
            }
        }
        /// <summary>
        /// 提取无导电布三层坐标
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="ordinates"></param>
        public void WudaodianbuSanceng(Mat gray, out List<int> ordinates)
        {
            ordinates = new List<int>();

            //图像处理
            Mat filter = new Mat();
            Cv2.GaussianBlur(gray, filter, new Size(9, 9), 3);
            Mat sobel = new Mat();
            EdgeY2(filter, out sobel);
            Mat threshSobel = new Mat();
            threshSobel = sobel.Threshold(80, 1, ThresholdTypes.Binary);

            Mat thresh = new Mat();
            thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 7));
            Cv2.MorphologyEx(thresh, thresh, MorphTypes.Close, seClose);
            Mat fill = new Mat();
            Fill(thresh, out fill, 1);
            Mat fanse = 1 - fill;

            Mat and = new Mat();
            Cv2.BitwiseAnd(fanse, threshSobel, and);

            //Mat seClose2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 1));
            //Mat close2 = new Mat();
            //Cv2.MorphologyEx(and, close2, MorphTypes.Close, seClose2);
            Mat nomin = new Mat();
            GetArea(and, out nomin, 2000, true);
            //ImageShow(threshSobel * 255, thresh * 255, and * 255, nomin * 255 + gray);
            //坐标提取
            Mat result = nomin.Clone();
            int middle = result.Cols / 2;
            Scalar sum = new Scalar();
            for (int i = 0; i < result.Rows - 1; i++)
            {
                sum = result[i, i + 2, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Add(newOrdinate + 5);
                    i += 30;
                }
            }
            if (ordinates[1] - ordinates[0] > 300)
            {
                if (ordinates[2] - ordinates[1] > 120)
                {
                    for (int i = ordinates[1] + 30; i < ordinates[2]; i++)
                    {
                        sum = result[i, i + 2, 0, result.Cols].Sum();
                        if ((int)sum > 100)
                        {
                            int newOrdinate = i;
                            ordinates.Insert(2, newOrdinate);
                            break;
                        }
                    }
                }
            }
            else
            {
                if (ordinates[3] - ordinates[2] > 120)
                {
                    for (int i = ordinates[2] + 30; i < ordinates[3]; i++)
                    {
                        sum = result[i, i + 2, 0, result.Cols].Sum();
                        if ((int)sum > 100)
                        {
                            int newOrdinate = i;
                            ordinates.Insert(3, newOrdinate);
                            break;
                        }
                    }
                }
            }
            ////添加超出范围的线条
            //Mat stright = new Mat();
            //List<int> strights = new List<int>();
            //KeepStraight(result, out stright, out strights);
            ////插入原坐标没有的点
            //for (int i = 0; i < strights.Count; i++)
            //{
            //    for (int j = 0; j < ordinates.Count - 1; j++)
            //    {

            //        if (Math.Abs(strights[i] - ordinates[j]) < 30 || Math.Abs(strights[i] - ordinates[j + 1]) < 30)
            //            break;
            //        else if (strights[i] > ordinates[j] && strights[i] < ordinates[j + 1])
            //        {
            //            ordinates.Insert(j + 1, strights[i]);
            //            break;
            //        }
            //    }
            //}
            ////删除过近的坐标
            //List<int> ordinatesCopy = ordinates.ToList();
            //int count = 0;
            //for (int i = 0; i < ordinates.Count - 1; i++)
            //{
            //    if (ordinates[i + 1] - ordinates[i] < 10)
            //    {
            //        ordinatesCopy.RemoveAt(i - count);
            //        count++;
            //    }
            //}
            //ordinates = ordinatesCopy.ToList();
            //增加最下层坐标
            if (ordinates.Count < 10)
            {
                Mat bottom = gray.Clone();
                Cv2.Rectangle(bottom, new Rect(0, 0, bottom.Cols, ordinates[ordinates.Count - 1]), new Scalar(0), -1);
                Cv2.GaussianBlur(bottom, bottom, new Size(5, 5), 3);
                Mat edge = new Mat();
                EdgeY(bottom, out edge);
                Mat threshEdge = new Mat();
                threshEdge = edge.Threshold(30, 1, ThresholdTypes.Binary);
                Mat seClose3 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 1));
                Mat close = new Mat();
                Cv2.MorphologyEx(threshEdge, close, MorphTypes.Close, seClose3);
                Mat nomin3 = new Mat();
                GetArea(close, out nomin3, 500, true);
                //Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 1));
                //Mat open = new Mat();
                //Cv2.MorphologyEx(threshEdge, open, MorphTypes.Open, seOpen);
                //ImageShow(threshEdge * 255,close*255,nomin3*255);
                Mat result2 = nomin3.Clone();
                for (int i = ordinates[ordinates.Count - 1] + 30; i < result2.Rows - 1; i++)
                {
                    sum = result2[i, i + 2, middle - 100, middle + 100].Sum();
                    if ((int)sum > 100)
                    {
                        int newOrdinate = i;
                        ordinates.Add(newOrdinate);
                        break;
                    }
                }
            }
            //else
            //{ 

            //}
        }
        /// <summary>
        /// 提取无导电布四层铜的坐标
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="ordinates"></param>
        public void WuDaodianbuSiceng(Mat gray, out List<int> ordinates)
        {
            ordinates = new List<int>();

            //图像处理
            Mat filter = new Mat();
            Cv2.GaussianBlur(gray, filter, new Size(5, 5), 3);
            Mat sobel = new Mat();
            EdgeY2(filter, out sobel);
            Mat threshSobel = new Mat();
            threshSobel = sobel.Threshold(60, 1, ThresholdTypes.Binary);

            Mat thresh = new Mat();
            thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 7));
            Cv2.MorphologyEx(thresh, thresh, MorphTypes.Close, seClose);
            Mat fill = new Mat();
            Fill(thresh, out fill, 1);
            Mat fanse = 1 - fill;

            Mat and = new Mat();
            Cv2.BitwiseAnd(fanse, threshSobel, and);

            Mat seClose2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 1));
            Mat close2 = new Mat();
            Cv2.MorphologyEx(and, close2, MorphTypes.Close, seClose2);
            Mat nomin = new Mat();
            GetArea(close2, out nomin, 2000, true);
            //ImageShow(threshSobel * 255, thresh * 255, and * 255, nomin * 255 + gray);
            //坐标提取
            Mat result = nomin.Clone();
            int middle = result.Cols / 2;
            Scalar sum = new Scalar();
            for (int i = 0; i < result.Rows - 1; i++)
            {
                sum = result[i, i + 2, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Add(newOrdinate + 5);
                    i += 30;
                }
            }
        }
        /// <summary>
        /// 提取有内部线条的坐标
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="ordinates"></param>
        public void WuDaodianbuQicengtong(Mat gray, out List<int> ordinates)
        {
            ordinates = new List<int>();

            //图像处理
            Mat filter = new Mat();
            Cv2.GaussianBlur(gray, filter, new Size(9, 9), 3);
            Mat sobel = new Mat();
            EdgeY2(filter, out sobel);
            Mat threshSobel = new Mat();
            threshSobel = sobel.Threshold(80, 1, ThresholdTypes.Binary);

            Mat thresh = new Mat();
            thresh = gray.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 7));
            Cv2.MorphologyEx(thresh, thresh, MorphTypes.Close, seClose);
            Mat fill = new Mat();
            Fill(thresh, out fill, 1);
            Mat fanse = 1 - fill;

            Mat and = new Mat();
            Cv2.BitwiseAnd(fanse, threshSobel, and);

            Mat nomin = new Mat();
            GetArea(and, out nomin, 2000, true);

            Mat threshSobel2 = new Mat();
            threshSobel2 = sobel.Threshold(180, 1, ThresholdTypes.Binary);
            //ImageShow(threshSobel * 255, and * 255, nomin * 255 + gray,threshSobel2*255);
            //坐标提取
            Mat result = nomin.Clone();
            int middle = result.Cols / 2;
            Scalar sum = new Scalar();
            for (int i = 0; i < result.Rows - 1; i++)
            {
                sum = result[i, i + 2, middle - 100, middle + 100].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Add(newOrdinate + 5);
                    i += 30;
                }
            }
            //对内部线进行提取
            //对内部进行阈值分割
            int start1 = ordinates[0];
            int start2 = ordinates[2];
            Mat crop1 = gray[ordinates[0], ordinates[1], middle - 100, middle + 100].Clone();
            Mat crop2 = gray[ordinates[2], ordinates[3], middle - 100, middle + 100].Clone();
            Mat threshCrop1 = 1 - crop1.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat threshCrop2 = 1 - crop2.Threshold(0, 1, ThresholdTypes.Otsu);
            //ImageShow(threshCrop1 * 255, threshCrop2 * 255);
            for (int i = 10; i < threshCrop1.Rows - 1; i++)
            {
                sum = threshCrop1[i, i + 2, 0, threshCrop1.Cols].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Insert(1, newOrdinate + ordinates[0]);
                    break;
                }
            }
            for (int i = threshCrop1.Rows - 30; i > 2; i--)
            {
                sum = threshCrop1[i - 2, i, 0, threshCrop1.Cols].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Insert(2, newOrdinate + ordinates[0]);
                    break;
                }
            }
            for (int i = 30; i < threshCrop2.Rows - 2; i++)
            {
                sum = threshCrop2[i, i + 2, 0, threshCrop2.Cols].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Insert(5, newOrdinate + start2);
                    break;
                }
            }
            for (int i = threshCrop2.Rows - 10; i > 2; i--)
            {
                sum = threshCrop2[i - 2, i, 0, threshCrop2.Cols].Sum();
                if ((int)sum > 100)
                {
                    int newOrdinate = i;
                    ordinates.Insert(6, newOrdinate + start2);
                    break;
                }
            }
        }
        /// <summary>
        /// 通过计算二值图最集中的区域来得到叠构的提取区域
        /// </summary>
        /// <param name="contour"></param>
        /// <param name="dataArea"></param>
        public void DiegouDataArea(Mat contour, out int dataArea)
        {
            Scalar sum = new Scalar(0);
            Scalar max = new Scalar(0);
            int maxArea = 0;
            for (int j = contour.Cols / 5; j < contour.Cols / 5 * 4 && j < contour.Cols - 40; j++)
            {
                sum = contour[0, contour.Rows, j, j + 40].Sum();
                if ((int)sum > (int)max)
                {
                    max = sum;
                    maxArea = j;
                }
            }
            dataArea = maxArea + 20;
        }
        /// <summary>
        /// 得到去噪后的边缘线
        /// </summary>
        /// <param name="image"></param>
        /// <param name="edge"></param>
        public void GetEdge(Mat image, out Mat edge)
        {
            Mat filter = new Mat();
            Cv2.GaussianBlur(image, filter, new Size(11, 11), 5, 5);
            edge = new Mat();
            Cv2.Canny(filter, edge, 10, 10);
            //去除小连通域噪声
            Mat[] contours;
            Mat hierachy = new Mat();
            Cv2.FindContours(edge, out contours, hierachy, RetrievalModes.External, ContourApproximationModes.ApproxNone);
            int area = 2;
            Mat noise = Mat.Zeros(edge.Rows, edge.Cols, edge.Type());
            for (int i = 0; i < contours.Count(); i++)
            {
                if (Cv2.ContourArea(contours[i]) > area)
                {
                    Cv2.DrawContours(noise, contours, i, new Scalar(1));
                }
            }
            //减去噪声+开运算
            Mat noNoise = edge - noise * 255;
            //Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            //Mat close = new Mat();
            //Cv2.MorphologyEx(noNoise, close, MorphTypes.Close, seClose);
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 1));
            Mat open = new Mat();
            Cv2.MorphologyEx(noNoise, open, MorphTypes.Open, seOpen);
            edge = open;

        }
        /// <summary>
        /// 计算线的坐标，当10行内点的数量大于10时记录平均坐标，用的是非膨胀后开运算结果图
        /// </summary>
        /// <param name="edge"></param>
        /// <param name="dataArea"></param>
        /// <param name="ordinates"></param>
        public void GetOrdinate(Mat edge, int dataArea, out List<int> ordinates)
        {
            int upper = 0;
            int lower = 0;
            int upperBound = 0, lowerBound = 0;
            int count = 0;
            int meanOrdinate = 0;
            ordinates = new List<int>();
            Scalar sum = new Scalar(0);
            for (int i = 0; i < edge.Rows; i++)
            {
                sum = edge[i, i + 3, 0, edge.Cols].Sum();
                if ((int)sum > 50)
                {
                    upper = i;
                    break;
                }
            }
            for (int i = edge.Rows - 1; i > 0; i--)
            {
                sum = edge[i - 3, i, 0, edge.Cols].Sum();
                if ((int)sum > 40)
                {
                    lower = i;
                    break;
                }
            }
            upperBound = upper - 10;
            while (lowerBound < lower + 50)
            {
                count = 0;
                meanOrdinate = 0;
                while (count < 10 /*&& lowerBound + 20 < edge.Rows*/)
                {
                    upperBound += 5;
                    lowerBound = upperBound + 5;
                    for (int i = upperBound; i < lowerBound; i++)
                    {
                        for (int j = dataArea - 25; j < dataArea + 25; j++)
                        {
                            if (edge.Get<byte>(i, j) > 0)
                            {
                                meanOrdinate += i;
                                count++;
                            }
                        }
                    }
                }
                if (count > 5)
                {
                    int newOrdinate = new int();
                    newOrdinate = meanOrdinate / count;
                    if (ordinates.Count > 0 && newOrdinate > ordinates[ordinates.Count - 1] + 40)
                    {
                        ordinates.Add(newOrdinate);
                        upper += 10;
                    }
                    else if (ordinates.Count == 0)
                    {
                        ordinates.Add(newOrdinate);
                        upper += 10;
                    }
                }
            }
        }
        public void GetOrdinate2(Mat edge, int dataArea, out List<int> ordinates)
        {
            int upper = 0;
            int lower = 0;
            int upperBound = 0, lowerBound = 0;
            int count = 0;
            int meanOrdinate = 0;
            ordinates = new List<int>();
            Scalar sum = new Scalar(0);
            for (int i = 0; i < edge.Rows; i++)
            {
                sum = edge[i, i + 3, 0, edge.Cols].Sum();
                if ((int)sum > 70)
                {
                    upper = i;
                    break;
                }
            }
            for (int i = edge.Rows - 1; i > 0; i--)
            {
                sum = edge[i - 3, i, 0, edge.Cols].Sum();
                if ((int)sum > 40)
                {
                    lower = i;
                    break;
                }
            }
            upperBound = upper - 10;
            int j = 0;
            while (upperBound + 20 < lower)
            {
                for (int i = upperBound; i < lower + 50; i += 1)
                {
                    sum = edge[i, i + 5, dataArea - 50, dataArea + 50].Sum();
                    if ((int)sum > 10)
                    {
                        meanOrdinate = i + 1;
                        if (ordinates.Count == 0)
                        {
                            ordinates.Add(meanOrdinate);
                            upperBound = i + 10;
                            break;
                        }
                        else if (ordinates.Count > 0 && meanOrdinate > ordinates[ordinates.Count - 1] + 40)
                        {
                            ordinates.Add(meanOrdinate);
                            upperBound = (i + 10);
                            break;
                        }

                    }
                    j = i;
                }
                if (j == lower + 49)
                    break;
            }
        }
        /// <summary>
        /// 对叠构的上区域重新进行处理并判断是否有线条存在
        /// </summary>
        /// <param name="image"></param>
        /// <param name="ordinate"></param>
        /// <param name="border"></param>
        public void UpperProcess(Mat image, out int ordinate, int[] border)
        {
            ordinate = 0;
            Mat result = new Mat();
            Mat crop = image[border[0], border[1], 0, image.Cols].Clone();
            //ImageShow(crop);
            Cv2.GaussianBlur(crop, crop, new Size(11, 11), 5, 5);
            //ImageShow(crop);
            //Cv2.MedianBlur(image, image, 11);
            //ImageShow(image);
            Mat edgeSobel = new Mat();
            EdgeY(crop, out edgeSobel);
            //Sobel(image, out edgeSobel);
            Mat threshEdge = new Mat();
            double t2 = Cv2.Threshold(edgeSobel, threshEdge, 0, 255, ThresholdTypes.Otsu);
            threshEdge = edgeSobel.Threshold(15, 255, ThresholdTypes.Binary);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(9, 1));
            Mat close = new Mat();
            Cv2.MorphologyEx(threshEdge, close, MorphTypes.Close, seClose);
            close = close / 255;

            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(9, 1));
            Mat open = new Mat();
            Cv2.MorphologyEx(close, open, MorphTypes.Open, seOpen);
            GetArea(open, out close, 400, true);
            result = close.Clone();
            //ImageShow(crop, edgeSobel, threshEdge, result * 255);
            Scalar sum = new Scalar(0);
            for (int i = 0; i < crop.Rows - 5; i++)
            {
                sum = result[i, i + 2, result.Cols / 3, result.Cols / 3 * 2].Sum();
                if ((int)sum > result.Cols / 2)
                {
                    ordinate = i;
                    break;
                }
            }
        }
        public void DiegouImageProcess(Mat gray, out Mat result)
        {
            result = new Mat();
            //大致轮廓线
            Mat newGray = new Mat();
            Cv2.GaussianBlur(gray, newGray, new Size(15, 15), 5, 5);
            Mat filter = new Mat();
            //Cv2.MedianBlur(newGray, filter, 9);
            PointEnhancement(newGray, out filter);
            //Mat blur = new Mat();
            //Cv2.MedianBlur(filter, blur, 7);
            Mat edgeSobel = new Mat();
            Edge(filter, out edgeSobel);
            Mat threshEdge = new Mat();
            double t2 = Cv2.Threshold(edgeSobel, threshEdge, 0, 255, ThresholdTypes.Otsu);
            threshEdge = edgeSobel.Threshold(20, 255, ThresholdTypes.Binary);
            //Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 1));
            //Mat close = new Mat();
            //Cv2.MorphologyEx(threshEdge, close, MorphTypes.Close, seClose);
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(11, 1));
            Mat open = new Mat();
            Cv2.MorphologyEx(threshEdge, open, MorphTypes.Open, seOpen);
            Mat sobel4 = new Mat();
            Sobel(open, out sobel4);
            //Mat nomin = new Mat();
            //GetArea(open, out nomin, 20, true);
            //Mat nocircle = new Mat();
            //RemoveCircles(open, out nocircle);
            //ImageShow(edgeSobel, threshEdge, open/*, nocircle*255*/);
            //铜线
            Mat thresh = new Mat();
            thresh = gray.Threshold(0, 255, ThresholdTypes.Otsu);
            Mat fill = new Mat();
            Fill(thresh, out fill, 255);
            Mat edge2 = new Mat();
            Sobel(fill, out edge2);
            //铜内部线
            Mat edge3 = new Mat();
            Sobel(filter, out edge3);
            Mat thresh3 = edge3.Threshold(10, 255, ThresholdTypes.Binary);
            Mat and = new Mat();
            Cv2.BitwiseAnd(thresh, thresh3, and);
            Mat seErode = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(15, 3));
            Mat erode = new Mat();
            Cv2.Erode(and, erode, seErode);
            Mat seOpen2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 3));
            Mat open2 = new Mat();
            Cv2.MorphologyEx(and, open2, MorphTypes.Open, seOpen2);
            Mat nomin2 = new Mat();
            GetArea(open2, out nomin2, 200, true);
            //ImageShow( and,erode,open2,nomin2*255);
            //铜内部线2
            Mat and2 = new Mat();
            Cv2.BitwiseAnd(gray, thresh, and2);
            Scalar sum = and2.Sum();
            int num = 0;
            Mat idx = new Mat();
            Cv2.FindNonZero(and2, idx);
            num = idx.Rows;
            int T = (int)sum / num;
            Mat thresh4 = and2.Threshold(T, 255, ThresholdTypes.Binary);
            Mat seClose3 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 1));
            Mat close3 = new Mat();
            Cv2.MorphologyEx(thresh4, close3, MorphTypes.Close, seClose3);
            Mat fill2 = new Mat();
            Fill(close3, out fill2, 255);
            Mat nomin3 = new Mat();
            GetArea(fill2, out nomin3, 10000, true);
            Mat fanse = 255 - nomin3 * 255;
            Mat edge4 = new Mat();
            Sobel(fanse, out edge4);
            //ImageShow(thresh4, edge4);
            //最终
            Mat fanse2 = 255 - thresh;
            Mat and3 = new Mat();
            Cv2.BitwiseAnd(fanse2, sobel4, and3);
            result = and3 + edge2 + edge4;/*nomin2 * 255;*/
            //ImageShow(result);
        }
        public void DiegouImageProcess2(Mat gray, out Mat result)
        {
            result = new Mat();
            Mat filter = new Mat();
            Mat junheng = new Mat();
            Mat blur = new Mat();
            Mat zengqiang = new Mat();
            Mat edge = new Mat();
            Mat thresh = new Mat();
            //PointEnhancement(gray, out zengqiang);
            //Cv2.EqualizeHist(zengqiang, junheng);
            //Cv2.GaussianBlur(junheng, filter, new Size(15,15), 5, 5);
            ////PointEnhancement(filter, out zengqiang);
            //Cv2.Blur(filter, blur, new Size (3,3));
            //Cv2.GaussianBlur(gray, filter, new Size(15, 15), 5, 5);
            Cv2.Blur(gray, blur, new Size(3, 3));
            PointEnhancement(blur, out zengqiang);
            //Cv2.EqualizeHist(zengqiang, junheng);
            //ImageShow(gray, zengqiang, junheng, /*filter,*/blur);

            Edge(zengqiang, out edge);
            Mat threshEdge = edge.Threshold(30, 255, ThresholdTypes.Binary);
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 1));
            Mat open = new Mat();
            Cv2.MorphologyEx(threshEdge, open, MorphTypes.Open, seOpen);

            double t = Cv2.Threshold(gray, thresh, 0, 255, ThresholdTypes.Otsu);
            thresh = gray.Threshold(t - 20, 255, ThresholdTypes.Binary);
            Mat fill = new Mat();
            Fill(thresh, out fill, 255);
            Mat fanse = 255 - fill;
            Mat and = new Mat();
            Cv2.BitwiseAnd(fanse, open, and);
            //Mat seOpen2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 1));
            //Mat open2 = new Mat();
            //Cv2.MorphologyEx(and, open2, MorphTypes.Open, seOpen2);
            Mat nomin = new Mat();
            GetArea(and, out nomin, 500, true);
            gray = gray + nomin * 100;
            ImageShow(thresh, fill, fanse);
            ImageShow(and, nomin * 255, gray);

            //Cv2.Canny(filter, edge, 7, 0);
            //Mat nomin = new Mat();
            //GetArea(edge, out nomin, 5, true);
            //ImageShow(edge, nomin * 255);

            //CvTrackbarCallback cvTrackbarCallback = new CvTrackbarCallback(Text);
            //CvTrackbarCallback cvTrackbarCallback2 = new CvTrackbarCallback(Text2);
            //Window window = new Window("tbar");//创建一个新窗口"tbar"
            //CvTrackbar cvTrackbarV = new CvTrackbar("bar1", "tbar", 25, 500, cvTrackbarCallback);
            //CvTrackbar cvTrackbar2 = new CvTrackbar("bar2", "tbar", 35, 500, cvTrackbarCallback2);

            //Cv2.WaitKey();
            //void Text(int value)
            //{
            //    minValue = value;
            //    Cv2.Canny(filter, edge, minValue, maxValue);
            //    new Window("tbar", edge);
            //}
            //void Text2(int value)
            //{
            //    maxValue = value;
            //    Cv2.Canny(filter, edge, minValue, maxValue);
            //    new Window("tbar", edge);
            //}

            //CvTrackbarCallback cvTrackbarCallback = new CvTrackbarCallback(Text);
            //CvTrackbarCallback cvTrackbarCallback2 = new CvTrackbarCallback(Text2);

            //CvTrackbar cvTrackbarV = new CvTrackbar("bar1", "tbar", 25, 225, cvTrackbarCallback);
            //CvTrackbar cvTrackbar2 = new CvTrackbar("bar2", "tbar", 35, 225, cvTrackbarCallback2);

            //Cv2.WaitKey();
            //void Text(int value)
            //{
            //    color = value;
            //    Cv2.BilateralFilter(gray, filter, d, color, 3);
            //    PointEnhancement(filter, out zengqiang);
            //    Sobel(zengqiang, out edge);
            //    thresh = edge.Threshold(5, 255, ThresholdTypes.Binary);
            //    new Window("tbar", WindowMode.Normal, thresh);
            //}
            //void Text2(int value)
            //{
            //    d = value;
            //    Cv2.BilateralFilter(gray, filter, d, color, 3);
            //    PointEnhancement(filter, out zengqiang);
            //    Sobel(zengqiang, out edge);
            //    thresh = edge.Threshold(5, 255, ThresholdTypes.Binary);
            //    new Window("tbar", WindowMode.Normal, thresh);
            //}
        }
        public void DiegouImageProcess3(Mat gray, out Mat result, out Mat edgeSobel)
        {
            result = new Mat();
            //大致轮廓线
            Mat newGray = new Mat();
            Cv2.GaussianBlur(gray, newGray, new Size(11, 11), 3, 3);
            Mat blur = new Mat();
            Cv2.Blur(newGray, blur, new Size(3, 3));
            Mat filter = new Mat();
            PointEnhancement(blur, out filter);
            edgeSobel = new Mat();
            //Edge(filter, out edgeSobel);
            EdgeY2(filter, out edgeSobel);
            Mat threshEdge = new Mat();
            double t2 = Cv2.Threshold(edgeSobel, threshEdge, 0, 255, ThresholdTypes.Otsu);
            threshEdge = edgeSobel.Threshold(80, 255, ThresholdTypes.Binary);

            Mat thresh = gray.Threshold(0, 255, ThresholdTypes.Otsu);
            Mat fill = new Mat();
            Fill(thresh, out fill, 255);
            Mat sobel2 = new Mat();
            Sobel(fill, out sobel2);
            Mat fanse = 255 - fill;
            Mat and = new Mat();
            Cv2.BitwiseAnd(fanse, threshEdge, and);
            //ImageShow( threshEdge,sobel2, and,gray+and);

            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 1));
            Mat close = new Mat();
            Cv2.MorphologyEx(and, close, MorphTypes.Close, seClose);
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(7, 1));
            Mat open = new Mat();
            Cv2.MorphologyEx(close, open, MorphTypes.Open, seOpen);

            Mat nomin4 = new Mat();
            GetArea(open, out nomin4, 2000, true);
            Mat sobel4 = new Mat();
            Sobel(nomin4, out sobel4);
            //ImageShow(open,close,nomin4*255);
            result = sobel4 * 100 + sobel2;/*nomin2 * 255;*/
            //ImageShow(open,nomin4*255+gray ,result+gray);
        }
        public void DiegouImageProcess4(Mat gray, out Mat result)
        {
            result = new Mat(gray.Size(), gray.Type());
            int middle = gray.Cols / 2;
            Scalar sum = new Scalar();
            Scalar lastSum = new Scalar(0);
            byte[] cha = new byte[gray.Rows];
            for (int i = 0; i < gray.Rows; i++)
            {
                sum = gray[i, i + 1, middle - 200, middle + 200].Sum();
                if (i == 0)
                {
                    cha[i] = 0;
                }
                else
                {
                    cha[i] = (byte)Math.Abs((int)sum - (int)lastSum);
                }
                lastSum = sum;
            }
            for (int i = 0; i < gray.Rows; i++)
            {
                for (int j = 0; j < gray.Cols; j++)
                {
                    result.Set<byte>(i, j, cha[i]);
                }
            }
            ImageShow(result);
        }

        public void DiegouOrdinates(Mat image, Mat gray, Mat edgeSobel, bool daodianbu, out List<int> ordinates)
        {
            ordinates = new List<int>();
            Scalar sum = new Scalar(0);
            int middle = image.Cols / 2;
            image = image.Threshold(10, 1, ThresholdTypes.Binary);
            //Mat hierachy = new Mat();
            //Mat[] contoursMat;
            //Cv2.FindContours(image, out contoursMat, hierachy, RetrievalModes.External, ContourApproximationModes.ApproxNone);
            Mat thresh = gray.Threshold(0, 255, ThresholdTypes.Otsu);
            //ImageShow(thresh);
            int[] y = new int[4];
            int b = 0;
            for (int i = 0; i < thresh.Rows; i++)
            {
                sum = thresh[i, i + 1, 0, thresh.Cols].Sum();
                if ((int)sum > 50)
                {
                    y[0] = i;
                    break;
                }
            }
            for (int i = y[0] + 50; i < thresh.Rows; i++)
            {
                sum = thresh[i, i + 1, 0, thresh.Cols].Sum();
                if ((int)sum == 0)
                {
                    y[1] = i;
                    break;
                }
            }
            for (int i = y[1] + 50; i < thresh.Rows; i++)
            {
                sum = thresh[i, i + 1, 0, thresh.Cols].Sum();
                if ((int)sum > 50)
                {
                    y[2] = i;
                    break;
                }
            }
            for (int i = y[2]; i < thresh.Rows; i++)
            {
                sum = thresh[i, i + 1, 0, thresh.Cols].Sum();
                if ((int)sum == 0)
                {
                    y[3] = i;
                    break;
                }
            }
            Mat newThresh = thresh / 255;
            for (int j = 0; j < thresh.Cols; j++)
            {
                sum = newThresh[0, thresh.Rows, j, j + 1].Sum();
                if ((int)sum > 300)
                {
                    b = j;
                    break;
                }
            }
            int type = 0;
            int[] cha = new int[] { y[1] - y[0], y[3] - y[2], y[2] - y[1] };
            if ((y[1] - y[0]) > 180 && (y[3] - y[2]) > 180)
            {
                type = 1;//单独两个铜
            }
            else if (((cha[0] > 300) && y[2] == 0 && y[3] == 0 && b < thresh.Cols / 3) || ((cha[0] > 100 && cha[0] < 180) && (cha[1] > 100 && cha[1] < 180) && (cha[2] > 150)))
            {
                type = 2;//有内部线
            }
            if (type == 1)//当是只有两层铜的时候
            {
                for (int i = 0; i < image.Rows - 20; i++)
                {
                    sum = image[i, i + 2, middle - 100, middle + 100].Sum();
                    if ((int)sum > 150)
                    {
                        int newOrdinate = i;
                        ordinates.Add(newOrdinate /*+ 10*/);
                        i += 150;
                    }
                }
                if (ordinates.Count <= 3)
                {
                    ordinates.Clear();
                    for (int i = 0; i < image.Rows - 20; i++)
                    {
                        sum = image[i, i + 5, middle - 100, middle + 100].Sum();
                        if ((int)sum > 150)
                        {
                            int newOrdinate = i;
                            ordinates.Add(newOrdinate /*+ 10*/);
                            i += 150;
                        }
                    }
                }
            }
            else if (type == 2)
            {
                Mat threshEdge = edgeSobel.Threshold(180, 255, ThresholdTypes.Binary);
                Mat fanse = 255 - threshEdge;
                //ImageShow(threshEdge, fanse);
                for (int i = 0; i < image.Rows - 20; i++)
                {
                    sum = image[i, i + 2, middle - 100, middle + 100].Sum();
                    if ((int)sum > 150)
                    {
                        int newOrdinate = i;
                        ordinates.Add(newOrdinate + 10);
                        i += 30;
                    }
                }
                for (int i = ordinates[0]; i < ordinates[0] + 30; i++)
                {
                    sum = fanse[i, i + 2, middle - 100, middle + 100].Sum();
                    if ((int)sum > 50)
                    {
                        ordinates.Insert(1, i + 7);
                        break;
                    }
                }
                for (int i = ordinates[0] + 40; i < ordinates[2]; i++)
                {
                    sum = threshEdge[i, i + 2, middle - 100, middle + 100].Sum();
                    if ((int)sum > 150)
                    {
                        ordinates.Insert(2, i + 10);
                        break;
                    }
                }
                for (int i = ordinates[0] + 350; i < threshEdge.Rows; i++)
                {
                    sum = threshEdge[i, i + 2, middle - 100, middle + 100].Sum();
                    if ((int)sum > 150)
                    {
                        ordinates.Insert(5, i + 12);
                        break;
                    }
                }
                for (int i = ordinates[6] - 15; i > 0; i--)
                {
                    sum = fanse[i - 2, i, middle - 100, middle + 100].Sum();
                    if ((int)sum > 50)
                    {
                        ordinates.Insert(6, i - 7);
                        break;
                    }
                }
            }
            else
            {
                int t = 2;
                for (int i = 0; i < image.Rows - 20; i++)
                {
                    if (ordinates.Count == 0 && daodianbu)
                        t = 180;
                    else
                        t = 150;
                    sum = image[i, i + 2, middle - 100, middle + 100].Sum();
                    if ((int)sum > t)
                    {
                        int newOrdinate = i;
                        ordinates.Add(newOrdinate + 5);
                        i += 30;
                        //if (ordinates.Count == 1)
                        //    i += 10;
                        //else
                        //    i += 30;
                    }
                }
                ordinates[0] += 5;
                //ordinates[1] -= 5;
                Mat threshEdge = edgeSobel.Threshold(40, 1, ThresholdTypes.Binary);
                //ImageShow(threshEdge * 255);
                if (daodianbu)
                {
                    for (int i = ordinates[0] - 40; i < ordinates[0] - 10; i++)
                    {
                        sum = threshEdge[i, i + 2, middle - 50, middle + 50].Sum();
                        if ((int)sum > 75)
                        {
                            int newOrdinate = i;
                            ordinates.Insert(0, i);
                            break;
                        }
                    }
                    for (int i = ordinates[ordinates.Count - 1] + 40; i > ordinates[ordinates.Count - 1] + 10; i--)
                    {
                        sum = threshEdge[i - 2, i, middle - 50, middle + 50].Sum();
                        if ((int)sum > 75)
                        {
                            int newOrdinate = i;
                            ordinates.Add(i);
                            break;
                        }
                    }
                }
                //for (int i = ordinates[ordinates.Count-1] + 40; i > ordinates[ordinates.Count-1] + 5&&i<thresh.Rows-20; i--)
                //{
                //    sum = image[i-5, i , middle - 100, middle + 100].Sum();
                //    if ((int)sum > 100)
                //    {
                //        int newOrdinate = i;
                //        ordinates.Add(newOrdinate /*+ 10*/);
                //        break;
                //    }
                //}
                //for (int i = ordinates[0] - 40; i < ordinates[0] - 5; i++)
                //{
                //    sum = image[i , i+5, middle - 100, middle + 100].Sum();
                //    if ((int)sum > 100)
                //    {
                //        ordinates.Insert(0, i);
                //        break;
                //    }
                //}
                if (ordinates.Count <= 3)
                {
                    ordinates.Clear();
                    for (int i = 0; i < image.Rows - 20; i++)
                    {
                        sum = image[i, i + 5, middle - 100, middle + 100].Sum();
                        if ((int)sum > 150)
                        {
                            int newOrdinate = i;
                            ordinates.Add(newOrdinate /*+ 10*/);
                            i += 150;
                        }
                    }
                }
            }
        }
        public void DieGouTopBottom(Mat gray, out int ordinate, int[] range, string direction)
        {
            ordinate = 0;
            Mat crop = gray[range[0], range[1], gray.Cols / 2 - 100, gray.Cols / 2 + 100].Clone();

            Cv2.GaussianBlur(crop, crop, new Size(11, 11), 5, 5);

            Mat edgeSobel = new Mat();
            EdgeY(crop, out edgeSobel);
            Mat threshEdge = new Mat();
            double t2 = Cv2.Threshold(edgeSobel, threshEdge, 0, 255, ThresholdTypes.Otsu);
            threshEdge = edgeSobel.Threshold(15, 255, ThresholdTypes.Binary);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 1));
            Mat close = new Mat();
            Cv2.MorphologyEx(threshEdge, close, MorphTypes.Close, seClose);
            close = close / 255;

            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 1));
            Mat open = new Mat();
            Cv2.MorphologyEx(close, open, MorphTypes.Open, seOpen);
            GetArea(open, out close, 1000, true);
            Mat result = close.Clone();
            //ImageShow(crop, edgeSobel, threshEdge, result * 255);
            Scalar sum = new Scalar(0);
            switch (direction)
            {
                case "top":

                    for (int i = 0; i < crop.Rows - 10; i++)
                    {
                        sum = result[i, i + 2, 0, result.Cols].Sum();
                        if ((int)sum > 100)
                        {
                            ordinate = i;
                            break;
                        }
                    }
                    break;
                case "bottom":
                    for (int i = crop.Rows - 1; i > 2; i--)
                    {
                        sum = result[i - 2, i, 0, result.Cols].Sum();
                        if ((int)sum > 100)
                        {
                            ordinate = i;
                            break;
                        }
                    }
                    break;
            }
        }

        //锡膏
        //锡膏H

        public void XigaoKaikouXiangnei(Mat gray, int[] dataArea, int start, out int[] leftShangOrdinates, out int[] rightShangOrdinates, out int[] leftXiaOrdinates, out int[] rightXiaOrdinates)
        {
            leftShangOrdinates = new int[3];
            rightShangOrdinates = new int[3];
            leftXiaOrdinates = new int[3];
            rightXiaOrdinates = new int[3];

            #region//找上下边界
            int[] leftExtractionRange = new int[2];
            int[] rightExtractionRange = new int[2];
            Mat thresh = new Mat();
            double t = Cv2.Threshold(gray, thresh, 0, 1, ThresholdTypes.Otsu);
            thresh = gray.Threshold(t - 30, 1, ThresholdTypes.Binary);
            //ImageShow(thresh * 255);
            Scalar sum = new Scalar();
            Mat result1 = thresh.Clone();
            //for (int i = start; i < result1.Rows; i++)//左侧上界
            //{
            //    sum = result1[i, i + 1, dataArea[1]-350, dataArea[1] - 100].Sum();
            //    if ((int)sum > 100)
            //    {
            //        leftExtractionRange[0] = i;
            //        break;
            //    }
            //}
            for (int i = start; i < result1.Rows; i++)//左侧上界
            {
                //sum = result1[i, i + 1, dataArea[1] - 350, dataArea[1] - 100].Sum();
                if (result1.Get<byte>(i, dataArea[1] - 100) > 0)
                {
                    leftExtractionRange[0] = i;
                    break;
                }
            }
            for (int i = leftExtractionRange[0] + 50; i < result1.Rows; i++)//左侧下界
            {
                sum = result1[i, i + 1, dataArea[1] - 200, dataArea[1] - 100].Sum();
                if ((int)sum == 0)
                {
                    leftExtractionRange[1] = i;
                    break;
                }
            }
            //for (int i = start; i < result1.Rows; i++)//右侧上界
            //{
            //    sum = result1[i, i + 1, dataArea[2] + 100, dataArea[2]+350].Sum();
            //    if ((int)sum > 100)
            //    {
            //        rightExtractionRange[0] = i;
            //        break;
            //    }
            //}
            for (int i = start; i < result1.Rows; i++)//右侧上界
            {
                //sum = result1[i, i + 1, dataArea[2] + 100, dataArea[2] + 350].Sum();
                if (result1.Get<byte>(i, dataArea[2] + 100) > 0)
                {
                    rightExtractionRange[0] = i;
                    break;
                }
            }
            for (int i = rightExtractionRange[0] + 50; i < result1.Rows; i++)//右侧下界
            {
                sum = result1[i, i + 1, dataArea[2] + 100, dataArea[2] + 200].Sum();
                if ((int)sum == 0)
                {
                    rightExtractionRange[1] = i;
                    break;
                }
            }
            //LineShow(gray, dataArea[1], leftExtractionRange[0], dataArea[1], leftExtractionRange[1]);
            //LineShow(gray, dataArea[2], rightExtractionRange[0], dataArea[2], rightExtractionRange[1]);
            //ImageShow(gray);
            #endregion
            #region//找质量好的位置
            int[] maxSpacing = new int[2];
            Scalar max = new Scalar(0);
            for (int j = dataArea[1] - 300; j < dataArea[1]; j += 40)
            {
                sum = result1[leftExtractionRange[0], leftExtractionRange[1], j - 20, j + 20].Sum();
                if ((int)max < (int)sum)
                {
                    max = sum;
                    maxSpacing[0] = j;
                }
            }
            max = new Scalar(0);
            for (int j = dataArea[2]; j < dataArea[2] + 300; j += 40)
            {
                sum = result1[rightExtractionRange[0], rightExtractionRange[1], j - 20, j + 20].Sum();
                if ((int)max < (int)sum)
                {
                    max = sum;
                    maxSpacing[1] = j;
                }
            }
            //LineShow(gray, dataArea[0], start, dataArea[1], start);
            //LineShow(gray, dataArea[2], start, dataArea[3], start);
            //LineShow(gray, maxSpacing[0], leftExtractionRange[0], maxSpacing[0], leftExtractionRange[1]);
            //LineShow(gray, maxSpacing[1], rightExtractionRange[0], maxSpacing[1], rightExtractionRange[1]);
            //ImageShow(gray);
            #endregion
            Mat sobel = new Mat();
            Sobel(thresh, out sobel);
            Mat nomin = new Mat();
            GetArea(sobel, out nomin, 500, true);
            Mat result = nomin.Clone();
            #region//左上
            for (int i = leftExtractionRange[0] - 30; i < leftExtractionRange[0]; i++)
            {
                sum = result[i, i + 1, dataArea[1] - 350, dataArea[1] - 100].Sum();
                if ((int)sum > 0)
                {
                    leftShangOrdinates[1] = i;
                    break;
                }
            }
            //if (leftExtractionRange[0] - leftShangOrdinates[1] < 5)
            //    leftShangOrdinates[1] = 0;
            if (leftShangOrdinates[1] != 0)
            {
                for (int j = dataArea[1] - 350; j < dataArea[1] - 100; j++)
                {
                    if (result.Get<byte>(leftShangOrdinates[1], j) > 0)
                    {
                        leftShangOrdinates[0] = j;
                        leftShangOrdinates[2] = leftExtractionRange[0];
                        break;
                    }
                }
            }
            #endregion
            #region //右上
            for (int i = rightExtractionRange[0] - 30; i < rightExtractionRange[0]; i++)
            {
                sum = result[i, i + 1, dataArea[2] + 100, dataArea[2] + 350].Sum();
                if ((int)sum > 0)
                {
                    rightShangOrdinates[1] = i;
                    break;
                }
            }
            //if (rightExtractionRange[0] - rightShangOrdinates[1] < 5)
            //    rightShangOrdinates[1] = 0;
            if (rightShangOrdinates[1] != 0)
            {
                for (int j = dataArea[2] + 100; j < dataArea[2] + 350; j++)
                {
                    if (result.Get<byte>(rightShangOrdinates[1], j) > 0)
                    {
                        rightShangOrdinates[0] = j;
                        rightShangOrdinates[2] = rightExtractionRange[0];
                        break;
                    }
                }
            }
            #endregion
            Mat zengqiang = new Mat();
            PointEnhancement(gray, out zengqiang);
            Mat sobel2 = new Mat();
            //EdgeY2(gray, out sobel2);
            EdgeY2(zengqiang, out sobel2);
            Mat thresh2 = new Mat();
            thresh2 = sobel2.Threshold(200, 1, ThresholdTypes.Binary);
            Cv2.Rectangle(thresh2, new Rect(maxSpacing[0], 0, 1, thresh2.Rows), new Scalar(0), -1);
            Cv2.Rectangle(thresh2, new Rect(maxSpacing[1], 0, 1, thresh2.Rows), new Scalar(0), -1);
            Mat nomin2 = new Mat();
            GetArea(thresh2, out nomin2, 50, true);
            Mat result2 = nomin2.Clone();
            //ImageShow(nomin2 * 255);
            #region//左下
            int compensate = 5;
            for (int i = leftExtractionRange[0] + 20; i < leftExtractionRange[1] - 20; i++)
            {
                sum = result2[i, i + 1, maxSpacing[0] - 20, maxSpacing[0] + 20].Sum();
                if ((int)sum > 20)
                {
                    leftXiaOrdinates[1] = i;
                    break;
                }
            }
            for (int i = leftXiaOrdinates[1] + 20; i < leftExtractionRange[1] - 20; i++)
            {
                sum = result2[i, i + 1, maxSpacing[0] - 20, maxSpacing[0] + 20].Sum();
                if ((int)sum > 20)
                {
                    leftXiaOrdinates[2] = i;
                    break;
                }
            }
            leftXiaOrdinates[0] = maxSpacing[0];
            leftXiaOrdinates[1] += compensate;
            #endregion
            #region//右下
            for (int i = rightExtractionRange[0] + 20; i < rightExtractionRange[1] - 20; i++)
            {
                sum = result2[i, i + 1, maxSpacing[1] - 20, maxSpacing[1] + 20].Sum();
                if ((int)sum > 20)
                {
                    rightXiaOrdinates[1] = i;
                    break;
                }
            }
            for (int i = rightXiaOrdinates[1] + 20; i < rightExtractionRange[1] - 20; i++)
            {
                sum = result2[i, i + 1, maxSpacing[1] - 20, maxSpacing[1] + 20].Sum();
                if ((int)sum > 20)
                {
                    rightXiaOrdinates[2] = i;
                    break;
                }
            }
            rightXiaOrdinates[0] = maxSpacing[1];
            rightXiaOrdinates[1] += compensate;
            #endregion
            #region//下层迭代
            if (leftXiaOrdinates[2] == 0 || rightXiaOrdinates[2] == 0)
            {

                int leftThresh = 200, rightThresh = 200;
                while (leftXiaOrdinates[2] == 0)
                {
                    if (leftThresh == 0)
                        break;
                    leftThresh -= 10;
                    thresh2 = sobel2.Threshold(leftThresh, 1, ThresholdTypes.Binary);
                    Cv2.Rectangle(thresh2, new Rect(maxSpacing[0], 0, 1, thresh2.Rows), new Scalar(0), -1);
                    GetArea(thresh2, out nomin2, 500, true);
                    for (int i = leftXiaOrdinates[1] + 20; i < leftExtractionRange[1] - 10; i++)
                    {
                        sum = nomin2[i, i + 1, maxSpacing[0] - 20, maxSpacing[0] + 20].Sum();
                        if ((int)sum > 20)
                        {
                            leftXiaOrdinates[2] = i;
                            break;
                        }
                    }
                }
                while (rightXiaOrdinates[2] == 0)
                {
                    if (rightThresh == 0)
                        break;
                    rightThresh -= 10;
                    thresh2 = sobel2.Threshold(rightThresh, 1, ThresholdTypes.Binary);
                    Cv2.Rectangle(thresh2, new Rect(maxSpacing[1], 0, 1, thresh2.Rows), new Scalar(0), -1);
                    GetArea(thresh2, out nomin2, 500, true);
                    for (int i = rightXiaOrdinates[1] + 20; i < rightExtractionRange[1] - 10; i++)
                    {
                        sum = nomin2[i, i + 1, maxSpacing[1] - 20, maxSpacing[1] + 20].Sum();
                        if ((int)sum > 20)
                        {
                            rightXiaOrdinates[2] = i;
                            break;
                        }
                    }
                }

            }
            #endregion
            if (leftShangOrdinates[2] - leftShangOrdinates[1] < 5)
            {
                leftShangOrdinates[0] = 0;
                leftShangOrdinates[1] = 0;
                leftShangOrdinates[2] = 0;
            }
            if (rightShangOrdinates[2] - rightShangOrdinates[1] < 5)
            {
                rightShangOrdinates[0] = 0;
                rightShangOrdinates[1] = 0;
                rightShangOrdinates[2] = 0;
            }
            //LineShow(gray, leftXiaOrdinates[0], leftXiaOrdinates[1], leftXiaOrdinates[0], leftXiaOrdinates[2]);
            //LineShow(gray, rightXiaOrdinates[0], rightXiaOrdinates[1], rightXiaOrdinates[0], rightXiaOrdinates[2]);
            //ImageShow(gray);
        }
        public void XigaoYouheikuai(Mat gray, int[] dataArea, int start, out int[] leftShangOrdinates, out int[] rightShangOrdinates, out int[] leftXiaOrdinates, out int[] rightXiaOrdinates)
        {
            leftShangOrdinates = new int[3];
            rightShangOrdinates = new int[3];
            leftXiaOrdinates = new int[3];
            rightXiaOrdinates = new int[3];

            #region//提取上下边界与黑框边界
            int[] leftExtractionRange = new int[2];
            int[] rightExtractionRange = new int[2];
            int[] blackBorder = new int[2];

            Mat thresh = new Mat();
            double t = Cv2.Threshold(gray, thresh, 0, 1, ThresholdTypes.Otsu);
            thresh = gray.Threshold(t - 30, 1, ThresholdTypes.Binary);
            Scalar sum = new Scalar();
            Mat result1 = thresh.Clone();
            for (int i = start; i < result1.Rows; i++)//左侧上界
            {
                sum = result1[i, i + 1, dataArea[0], dataArea[1] - 100].Sum();
                if ((int)sum > 100)
                {
                    leftExtractionRange[0] = i;
                    break;
                }
            }
            for (int i = leftExtractionRange[0]; i < result1.Rows; i++)//左侧下界
            {
                sum = result1[i, i + 1, dataArea[0], dataArea[1] - 100].Sum();
                if ((int)sum == 0)
                {
                    leftExtractionRange[1] = i;
                    break;
                }
            }
            for (int i = start; i < result1.Rows; i++)//右侧上界
            {
                sum = result1[i, i + 1, dataArea[2] + 100, dataArea[3]].Sum();
                if ((int)sum > 100)
                {
                    rightExtractionRange[0] = i;
                    break;
                }
            }
            for (int i = rightExtractionRange[0]; i < result1.Rows; i++)//右侧下界
            {
                sum = result1[i, i + 1, dataArea[2] + 100, dataArea[3]].Sum();
                if ((int)sum == 0)
                {
                    rightExtractionRange[1] = i;
                    break;
                }
            }
            Mat sobel = new Mat();
            Sobel(gray, out sobel);
            Mat threshSobel = new Mat();
            threshSobel = sobel.Threshold(10, 1, ThresholdTypes.Binary);
            Mat nomin4 = new Mat();
            GetArea(threshSobel, out nomin4, 500, true);
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Mat open = new Mat();
            Cv2.MorphologyEx(threshSobel, open, MorphTypes.Open, seOpen);
            //ImageShow(threshSobel*255, nomin4 * 255);
            Mat result2 = nomin4.Clone();
            for (int j = dataArea[0]; j < dataArea[1]; j++)//提取左黑块边界
            {
                sum = result2[leftExtractionRange[0] - 100, leftExtractionRange[0] - 10, j, j + 1].Sum();
                if ((int)sum > 20)
                {
                    blackBorder[0] = j;
                    break;
                }
            }
            for (int j = dataArea[3]; j > dataArea[2]; j--)//提取右黑块边界
            {
                sum = result2[rightExtractionRange[0] - 100, rightExtractionRange[0] - 10, j - 1, j].Sum();
                if ((int)sum > 20)
                {
                    blackBorder[1] = j;
                    break;
                }
            }
            //LineShow(gray, dataArea[0], leftExtractionRange[0], dataArea[0], leftExtractionRange[1]);
            //LineShow(gray, dataArea[2], rightExtractionRange[0], dataArea[2], rightExtractionRange[1]);
            //LineShow(gray, blackBorder[0], leftExtractionRange[0] - 100, blackBorder[0], leftExtractionRange[0] - 10);
            //LineShow(gray, blackBorder[1], rightExtractionRange[0] - 100, blackBorder[1], rightExtractionRange[0] - 10);
            //ImageShow(gray, threshSobel * 255,open*255);
            #endregion
            Mat thresh2 = new Mat();
            thresh2 = gray.Threshold(t - 30, 1, ThresholdTypes.Binary);
            Mat sobel2 = new Mat();
            Sobel(thresh2, out sobel2);
            Mat nomin3 = new Mat();
            GetArea(sobel2, out nomin3, 500, true);
            Mat result3 = nomin3.Clone();
            //ImageShow(nomin3 * 255);
            #region//左上
            for (int i = leftExtractionRange[0] - 30; i < leftExtractionRange[0]; i++)
            {
                sum = result3[i, i + 1, dataArea[0], blackBorder[0]].Sum();
                if ((int)sum > 0)
                {
                    leftShangOrdinates[1] = i;
                    break;
                }
            }
            if (leftShangOrdinates[1] != 0)
            {
                for (int j = dataArea[0]; j < blackBorder[0]; j++)
                {
                    if (result3.Get<byte>(leftShangOrdinates[1], j) > 0)
                    {
                        leftShangOrdinates[0] = j;
                        leftShangOrdinates[2] = leftExtractionRange[0];
                        break;
                    }
                }
            }
            #endregion
            #region//右上
            for (int i = rightExtractionRange[0] - 30; i < rightExtractionRange[0]; i++)
            {
                sum = result3[i, i + 1, blackBorder[1], dataArea[3]].Sum();
                if ((int)sum > 0)
                {
                    rightShangOrdinates[1] = i;
                    break;
                }
            }
            if (rightShangOrdinates[1] != 0)
            {
                for (int j = blackBorder[1]; j < dataArea[3]; j++)
                {
                    if (result3.Get<byte>(rightShangOrdinates[1], j) > 0)
                    {
                        rightShangOrdinates[0] = j;
                        rightShangOrdinates[2] = rightExtractionRange[0];
                        break;
                    }
                }
            }
            #endregion
            //LineShow(gray, leftShangOrdinates[0], leftShangOrdinates[1], leftShangOrdinates[0], leftShangOrdinates[2]);
            //LineShow(gray, rightShangOrdinates[0], rightShangOrdinates[1], rightShangOrdinates[0], rightShangOrdinates[2]);
            //ImageShow(gray, sobel2 * 255);
            #region //提取最大间距的位置
            int[] maxSpacing = new int[2];
            Scalar max = new Scalar(0);
            for (int j = blackBorder[0]; j < dataArea[1]; j += 40)
            {
                sum = result1[leftExtractionRange[0], leftExtractionRange[1], j - 20, j + 20].Sum();
                if ((int)max < (int)sum)
                {
                    max = sum;
                    maxSpacing[0] = j;
                }
            }
            max = new Scalar(0);
            for (int j = dataArea[2]; j < blackBorder[1]; j += 40)
            {
                sum = result1[rightExtractionRange[0], rightExtractionRange[1], j - 20, j + 20].Sum();
                if ((int)max < (int)sum)
                {
                    max = sum;
                    maxSpacing[1] = j;
                }
            }
            //LineShow(gray, maxSpacing[0], leftExtractionRange[0], maxSpacing[0], leftExtractionRange[1]);
            //LineShow(gray, maxSpacing[1], rightExtractionRange[0], maxSpacing[1], rightExtractionRange[1]);
            //ImageShow(gray);
            #endregion
            Mat sobel3 = new Mat();
            EdgeY2(gray, out sobel3);
            Mat thresh3 = new Mat();
            thresh3 = sobel3.Threshold(200, 1, ThresholdTypes.Binary);
            Cv2.Rectangle(thresh3, new Rect(maxSpacing[0], 0, 1, thresh3.Rows), new Scalar(0), -1);
            Cv2.Rectangle(thresh3, new Rect(maxSpacing[1], 0, 1, thresh3.Rows), new Scalar(0), -1);
            Mat nomin2 = new Mat();
            GetArea(thresh3, out nomin2, 500, true);
            //ImageShow(gray, thresh3 * 255,nomin2*255,gray+nomin2*100);
            #region//左下
            int compensate = 5;
            Mat result4 = nomin2.Clone();
            for (int i = leftExtractionRange[0] + 20; i < leftExtractionRange[1] - 20; i++)
            {
                sum = result4[i, i + 1, maxSpacing[0] - 20, maxSpacing[0] + 20].Sum();
                if ((int)sum > 20)
                {
                    leftXiaOrdinates[1] = i;
                    break;
                }
            }
            for (int i = leftXiaOrdinates[1] + 20; i < leftExtractionRange[1] - 20; i++)
            {
                sum = result4[i, i + 1, maxSpacing[0] - 20, maxSpacing[0] + 20].Sum();
                if ((int)sum > 20)
                {
                    leftXiaOrdinates[2] = i;
                    break;
                }
            }
            leftXiaOrdinates[0] = maxSpacing[0];
            leftXiaOrdinates[1] += compensate;
            #endregion
            #region//右下
            for (int i = rightExtractionRange[0] + 20; i < rightExtractionRange[1] - 20; i++)
            {
                sum = result4[i, i + 1, maxSpacing[1] - 20, maxSpacing[1] + 20].Sum();
                if ((int)sum > 20)
                {
                    rightXiaOrdinates[1] = i;
                    break;
                }
            }
            for (int i = rightXiaOrdinates[1] + 20; i < rightExtractionRange[1] - 20; i++)
            {
                sum = result4[i, i + 1, maxSpacing[1] - 20, maxSpacing[1] + 20].Sum();
                if ((int)sum > 20)
                {
                    rightXiaOrdinates[2] = i;
                    break;
                }
            }
            rightXiaOrdinates[0] = maxSpacing[1];
            rightXiaOrdinates[1] += compensate;
            #endregion
            #region//下层迭代
            if (leftXiaOrdinates[2] == 0 || rightXiaOrdinates[2] == 0)
            {
                int leftThresh = 200, rightThresh = 200;
                while (leftXiaOrdinates[2] == 0)
                {
                    if (leftThresh == 0)
                        break;
                    leftThresh -= 10;
                    thresh3 = sobel3.Threshold(leftThresh, 1, ThresholdTypes.Binary);
                    Cv2.Rectangle(thresh3, new Rect(maxSpacing[0], 0, 1, thresh3.Rows), new Scalar(0), -1);
                    GetArea(thresh3, out nomin2, 500, true);
                    for (int i = leftXiaOrdinates[1] + 20; i < leftExtractionRange[1] - 20; i++)
                    {
                        sum = nomin2[i, i + 1, maxSpacing[0] - 20, maxSpacing[0] + 20].Sum();
                        if ((int)sum > 20)
                        {
                            leftXiaOrdinates[2] = i;
                            break;
                        }
                    }
                }
                while (rightXiaOrdinates[2] == 0)
                {
                    if (rightThresh == 0)
                        break;
                    rightThresh -= 10;
                    thresh3 = sobel3.Threshold(rightThresh, 1, ThresholdTypes.Binary);
                    Cv2.Rectangle(thresh3, new Rect(maxSpacing[1], 0, 1, thresh3.Rows), new Scalar(0), -1);
                    GetArea(thresh3, out nomin2, 500, true);
                    for (int i = rightXiaOrdinates[1] + 20; i < rightExtractionRange[1] - 20; i++)
                    {
                        sum = nomin2[i, i + 1, maxSpacing[1] - 20, maxSpacing[1] + 20].Sum();
                        if ((int)sum > 20)
                        {
                            rightXiaOrdinates[2] = i;
                            break;
                        }
                    }
                }

            }
            #endregion
            //LineShow(gray, leftXiaOrdinates[0], leftXiaOrdinates[1], leftXiaOrdinates[0], leftXiaOrdinates[2]);
            //LineShow(gray, rightXiaOrdinates[0], rightXiaOrdinates[1], rightXiaOrdinates[0], rightXiaOrdinates[2]);
            //ImageShow(gray,nomin2*255);
        }
        public void XigaoXiangShangWanqu(Mat gray, int[] dataArea, int start, out int[] leftShangOrdinates, out int[] rightShangOrdinates, out int[] leftXiaOrdinates, out int[] rightXiaOrdinates)
        {
            leftShangOrdinates = new int[3];
            rightShangOrdinates = new int[3];
            leftXiaOrdinates = new int[3];
            rightXiaOrdinates = new int[3];

            #region//上下边界
            int[] leftExtractionRange = new int[2];
            int[] rightExtractionRange = new int[2];
            Mat thresh = new Mat();
            double t = Cv2.Threshold(gray, thresh, 0, 1, ThresholdTypes.Otsu);
            thresh = gray.Threshold(t - 30, 1, ThresholdTypes.Binary);
            //ImageShow(thresh * 255);
            Scalar sum = new Scalar();
            Mat result1 = thresh.Clone();

            for (int i = start + 300; i < result1.Rows; i++)//左侧上界
            {
                //sum = result1[i, i + 1, dataArea[1] - 350, dataArea[1] - 100].Sum();
                if (result1.Get<byte>(i, dataArea[1] + 50) > 0)
                {
                    leftExtractionRange[0] = i;
                    break;
                }
            }
            for (int i = leftExtractionRange[0] + 50; i < result1.Rows; i++)//左侧下界
            {
                sum = result1[i, i + 1, dataArea[1] - 200, dataArea[1] - 100].Sum();
                if ((int)sum == 0)
                {
                    leftExtractionRange[1] = i;
                    break;
                }
            }

            for (int i = start + 300; i < result1.Rows; i++)//右侧上界
            {
                //sum = result1[i, i + 1, dataArea[2] + 100, dataArea[2] + 350].Sum();
                if (result1.Get<byte>(i, dataArea[2] - 50) > 0)
                {
                    rightExtractionRange[0] = i;
                    break;
                }
            }
            for (int i = rightExtractionRange[0] + 50; i < result1.Rows; i++)//右侧下界
            {
                sum = result1[i, i + 1, dataArea[2] + 100, dataArea[2] + 200].Sum();
                if ((int)sum == 0)
                {
                    rightExtractionRange[1] = i;
                    break;
                }
            }
            //LineShow(gray, dataArea[1] + 50, leftExtractionRange[0], dataArea[1] + 50, leftExtractionRange[1]);
            //LineShow(gray, dataArea[2] - 50, rightExtractionRange[0], dataArea[2] - 50, rightExtractionRange[1]);
            //ImageShow(gray);
            #endregion
            #region//找质量好的位置
            int[] maxSpacing = new int[2];
            Scalar max = new Scalar(0);
            for (int j = dataArea[1] - 250; j < dataArea[1]; j += 40)
            {
                sum = result1[leftExtractionRange[0], leftExtractionRange[1], j - 20, j + 20].Sum();
                if ((int)max < (int)sum)
                {
                    max = sum;
                    maxSpacing[0] = j;
                }
            }
            max = new Scalar(0);
            for (int j = dataArea[2]; j < dataArea[2] + 250; j += 40)
            {
                sum = result1[rightExtractionRange[0], rightExtractionRange[1], j - 20, j + 20].Sum();
                if ((int)max < (int)sum)
                {
                    max = sum;
                    maxSpacing[1] = j;
                }
            }
            //LineShow(gray, dataArea[0], start, dataArea[1], start);
            //LineShow(gray, dataArea[2], start, dataArea[3], start);
            //LineShow(gray, maxSpacing[0], leftExtractionRange[0], maxSpacing[0], leftExtractionRange[1]);
            //LineShow(gray, maxSpacing[1], rightExtractionRange[0], maxSpacing[1], rightExtractionRange[1]);
            //ImageShow(gray);
            #endregion
            #region//左上
            for (int i = leftExtractionRange[0] - 50; i < leftExtractionRange[0]; i++)
            {
                sum = thresh[i, i + 1, dataArea[1] - 350, dataArea[1] - 100].Sum();
                if ((int)sum > 0)
                {
                    leftShangOrdinates[1] = i;
                    break;
                }
            }
            if (leftShangOrdinates[1] != 0)
            {
                for (int j = dataArea[1] - 350; j < dataArea[1] - 100; j++)
                {
                    if (thresh.Get<byte>(leftShangOrdinates[1], j) > 0)
                    {
                        leftShangOrdinates[0] = j;
                        leftShangOrdinates[2] = leftExtractionRange[0];
                        break;
                    }
                }
            }
            #endregion
            #region //右上
            for (int i = rightExtractionRange[0] - 50; i < rightExtractionRange[0]; i++)
            {
                sum = thresh[i, i + 1, dataArea[2] + 100, dataArea[2] + 350].Sum();
                if ((int)sum > 0)
                {
                    rightShangOrdinates[1] = i;
                    break;
                }
            }
            //if (rightExtractionRange[0] - rightShangOrdinates[1] < 5)
            //    rightShangOrdinates[1] = 0;
            if (rightShangOrdinates[1] != 0)
            {
                for (int j = dataArea[2] + 100; j < dataArea[2] + 350; j++)
                {
                    if (thresh.Get<byte>(rightShangOrdinates[1], j) > 0)
                    {
                        rightShangOrdinates[0] = j;
                        rightShangOrdinates[2] = rightExtractionRange[0];
                        break;
                    }
                }
            }
            #endregion
            //LineShow(gray, leftShangOrdinates[0], leftShangOrdinates[1], leftShangOrdinates[0], leftShangOrdinates[2]);
            //LineShow(gray, rightShangOrdinates[0], rightShangOrdinates[1], rightShangOrdinates[0], rightShangOrdinates[2]);
            //ImageShow(gray);

            Mat zengqiang = new Mat();
            PointEnhancement(gray, out zengqiang);
            Mat sobel2 = new Mat();
            //EdgeY2(gray, out sobel2);
            EdgeY2(zengqiang, out sobel2);
            Mat thresh2 = new Mat();
            thresh2 = sobel2.Threshold(200, 1, ThresholdTypes.Binary);
            Cv2.Rectangle(thresh2, new Rect(maxSpacing[0], 0, 1, thresh2.Rows), new Scalar(0), -1);
            Cv2.Rectangle(thresh2, new Rect(maxSpacing[1], 0, 1, thresh2.Rows), new Scalar(0), -1);
            Mat nomin2 = new Mat();
            GetArea(thresh2, out nomin2, 50, true);
            Mat result2 = nomin2.Clone();
            //ImageShow(nomin2 * 255);
            #region//左下
            int compensate = 5;
            for (int i = leftExtractionRange[0] + 20; i < leftExtractionRange[1] - 40; i++)
            {
                sum = result2[i, i + 1, maxSpacing[0] - 20, maxSpacing[0] + 20].Sum();
                if ((int)sum > 20)
                {
                    leftXiaOrdinates[1] = i;
                    break;
                }
            }
            for (int i = leftXiaOrdinates[1] + 20; i < leftExtractionRange[1] - 20; i++)
            {
                sum = result2[i, i + 1, maxSpacing[0] - 20, maxSpacing[0] + 20].Sum();
                if ((int)sum > 20)
                {
                    leftXiaOrdinates[2] = i;
                    break;
                }
            }
            leftXiaOrdinates[0] = maxSpacing[0];
            leftXiaOrdinates[1] += compensate;
            #endregion
            #region//右下
            for (int i = rightExtractionRange[0] + 20; i < rightExtractionRange[1] - 40; i++)
            {
                sum = result2[i, i + 1, maxSpacing[1] - 20, maxSpacing[1] + 20].Sum();
                if ((int)sum > 20)
                {
                    rightXiaOrdinates[1] = i;
                    break;
                }
            }
            for (int i = rightXiaOrdinates[1] + 20; i < rightExtractionRange[1] - 20; i++)
            {
                sum = result2[i, i + 1, maxSpacing[1] - 20, maxSpacing[1] + 20].Sum();
                if ((int)sum > 20)
                {
                    rightXiaOrdinates[2] = i;
                    break;
                }
            }
            rightXiaOrdinates[0] = maxSpacing[1];
            rightXiaOrdinates[1] += compensate;
            #endregion
            #region//下层迭代
            if (leftXiaOrdinates[1] < 10 || rightXiaOrdinates[1] < 10)
            {
                int leftThresh = 200, rightThresh = 200;
                while (leftXiaOrdinates[1] < 10)
                {
                    if (leftThresh == 0)
                        break;
                    leftThresh -= 10;
                    thresh2 = sobel2.Threshold(leftThresh, 1, ThresholdTypes.Binary);
                    Cv2.Rectangle(thresh2, new Rect(maxSpacing[0], 0, 1, thresh2.Rows), new Scalar(0), -1);
                    GetArea(thresh2, out nomin2, 500, true);
                    for (int i = leftExtractionRange[0] + 20; i < leftExtractionRange[1] - 30; i++)
                    {
                        sum = nomin2[i, i + 1, maxSpacing[0] - 20, maxSpacing[0] + 20].Sum();
                        if ((int)sum > 20)
                        {
                            leftXiaOrdinates[1] = i;
                            break;
                        }
                    }
                }
                for (int i = leftXiaOrdinates[1] + 20; i < leftExtractionRange[1] - 10; i++)
                {
                    sum = result2[i, i + 1, maxSpacing[0] - 20, maxSpacing[0] + 20].Sum();
                    if ((int)sum > 20)
                    {
                        leftXiaOrdinates[2] = i;
                        break;
                    }
                }
                while (rightXiaOrdinates[1] < 10)
                {
                    if (rightThresh == 0)
                        break;
                    rightThresh -= 10;
                    thresh2 = sobel2.Threshold(rightThresh, 1, ThresholdTypes.Binary);
                    Cv2.Rectangle(thresh2, new Rect(maxSpacing[1], 0, 1, thresh2.Rows), new Scalar(0), -1);
                    GetArea(thresh2, out nomin2, 500, true);
                    for (int i = rightExtractionRange[0] + 20; i < rightExtractionRange[1] - 30; i++)
                    {
                        sum = nomin2[i, i + 1, maxSpacing[1] - 20, maxSpacing[1] + 20].Sum();
                        if ((int)sum > 20)
                        {
                            rightXiaOrdinates[1] = i;
                            break;
                        }
                    }
                }
                for (int i = rightXiaOrdinates[1] + 20; i < rightExtractionRange[1] - 10; i++)
                {
                    sum = result2[i, i + 1, maxSpacing[1] - 20, maxSpacing[1] + 20].Sum();
                    if ((int)sum > 20)
                    {
                        rightXiaOrdinates[2] = i;
                        break;
                    }
                }
            }
            if (leftXiaOrdinates[2] == 0 || rightXiaOrdinates[2] == 0)
            {

                int leftThresh = 200, rightThresh = 200;
                while (leftXiaOrdinates[2] == 0)
                {
                    if (leftThresh == 0)
                        break;
                    leftThresh -= 10;
                    thresh2 = sobel2.Threshold(leftThresh, 1, ThresholdTypes.Binary);
                    Cv2.Rectangle(thresh2, new Rect(maxSpacing[0], 0, 1, thresh2.Rows), new Scalar(0), -1);
                    GetArea(thresh2, out nomin2, 500, true);
                    for (int i = leftXiaOrdinates[1] + 20; i < leftExtractionRange[1] - 10; i++)
                    {
                        sum = nomin2[i, i + 1, maxSpacing[0] - 20, maxSpacing[0] + 20].Sum();
                        if ((int)sum > 20)
                        {
                            leftXiaOrdinates[2] = i;
                            break;
                        }
                    }
                }
                while (rightXiaOrdinates[2] == 0)
                {
                    if (rightThresh == 0)
                        break;
                    rightThresh -= 10;
                    thresh2 = sobel2.Threshold(rightThresh, 1, ThresholdTypes.Binary);
                    Cv2.Rectangle(thresh2, new Rect(maxSpacing[1], 0, 1, thresh2.Rows), new Scalar(0), -1);
                    GetArea(thresh2, out nomin2, 500, true);
                    for (int i = rightXiaOrdinates[1] + 20; i < rightExtractionRange[1] - 10; i++)
                    {
                        sum = nomin2[i, i + 1, maxSpacing[1] - 20, maxSpacing[1] + 20].Sum();
                        if ((int)sum > 20)
                        {
                            rightXiaOrdinates[2] = i;
                            break;
                        }
                    }
                }

            }
            #endregion
            //LineShow(gray, leftXiaOrdinates[0], leftXiaOrdinates[1], leftXiaOrdinates[0], leftXiaOrdinates[2]);
            //LineShow(gray, rightXiaOrdinates[0], rightXiaOrdinates[1], rightXiaOrdinates[0], rightXiaOrdinates[2]);
            //ImageShow(gray);
        }
        public void XigaoXiangXiaWanqu(Mat gray, int[] dataArea, int start, out int[] leftShangOrdinates, out int[] rightShangOrdinates, out int[] leftXiaOrdinates, out int[] rightXiaOrdinates)
        {
            leftShangOrdinates = new int[3];
            rightShangOrdinates = new int[3];
            leftXiaOrdinates = new int[3];
            rightXiaOrdinates = new int[3];
            #region//上下边界
            int[] leftExtractionRange = new int[2];
            int[] rightExtractionRange = new int[2];
            Mat thresh = new Mat();
            double t = Cv2.Threshold(gray, thresh, 0, 1, ThresholdTypes.Otsu);
            thresh = gray.Threshold(t - 30, 1, ThresholdTypes.Binary);
            //ImageShow(thresh * 255);
            Scalar sum = new Scalar();
            Mat result1 = thresh.Clone();

            for (int i = start + 300; i < result1.Rows; i++)//左侧上界
            {
                //sum = result1[i, i + 1, dataArea[1] - 350, dataArea[1] - 100].Sum();
                if (result1.Get<byte>(i, dataArea[1] - 50) > 0)
                {
                    leftExtractionRange[0] = i;
                    break;
                }
            }
            for (int i = leftExtractionRange[0] + 50; i < result1.Rows; i++)//左侧下界
            {
                sum = result1[i, i + 1, dataArea[0], dataArea[1] - 100].Sum();
                if ((int)sum < 100)
                {
                    leftExtractionRange[1] = i;
                    break;
                }
            }

            for (int i = start + 300; i < result1.Rows; i++)//右侧上界
            {
                //sum = result1[i, i + 1, dataArea[2] + 100, dataArea[2] + 350].Sum();
                if (result1.Get<byte>(i, dataArea[2] + 50) > 0)
                {
                    rightExtractionRange[0] = i;
                    break;
                }
            }
            for (int i = rightExtractionRange[0] + 50; i < result1.Rows; i++)//右侧下界
            {
                sum = result1[i, i + 1, dataArea[2] + 100, dataArea[3]].Sum();
                if ((int)sum < 100)
                {
                    rightExtractionRange[1] = i;
                    break;
                }
            }
            //LineShow(gray, dataArea[1] + 50, leftExtractionRange[0], dataArea[1] + 50, leftExtractionRange[1]);
            //LineShow(gray, dataArea[2] - 50, rightExtractionRange[0], dataArea[2] - 50, rightExtractionRange[1]);
            //ImageShow(gray);
            #endregion
            #region//找质量好的位置
            int[] maxSpacing = new int[2];
            Scalar max = new Scalar(0);
            for (int j = dataArea[1] - 300; j < dataArea[1]; j += 40)
            {
                sum = result1[leftExtractionRange[0], leftExtractionRange[1], j - 20, j + 20].Sum();
                if ((int)max < (int)sum)
                {
                    max = sum;
                    maxSpacing[0] = j;
                }
            }
            max = new Scalar(0);
            for (int j = dataArea[2]; j < dataArea[2] + 300; j += 40)
            {
                sum = result1[rightExtractionRange[0], rightExtractionRange[1], j - 20, j + 20].Sum();
                if ((int)max < (int)sum)
                {
                    max = sum;
                    maxSpacing[1] = j;
                }
            }
            //LineShow(gray, dataArea[0], start, dataArea[1], start);
            //LineShow(gray, dataArea[2], start, dataArea[3], start);
            //LineShow(gray, maxSpacing[0], leftExtractionRange[0], maxSpacing[0], leftExtractionRange[1]);
            //LineShow(gray, maxSpacing[1], rightExtractionRange[0], maxSpacing[1], rightExtractionRange[1]);
            //ImageShow(gray);
            #endregion
            //Mat zengqiang = new Mat();
            //PointEnhancement(gray, out zengqiang);
            Mat sobel3 = new Mat();
            EdgeY2(gray, out sobel3);
            Mat thresh3 = new Mat();
            thresh3 = sobel3.Threshold(200, 1, ThresholdTypes.Binary);
            Mat nomin3 = new Mat();
            GetArea(thresh3, out nomin3, 500, true);
            //ImageShow(thresh3 * 255,nomin3*255);
            Mat result3 = nomin3.Clone();
            #region//左上
            for (int i = leftExtractionRange[0] - 50; i < result3.Rows; i++)
            {
                if (result3.Get<byte>(i, dataArea[1] - 250) > 0)
                {
                    leftShangOrdinates[1] = i;
                    break;
                }
            }
            for (int i = leftShangOrdinates[1] + 50; i > leftShangOrdinates[1] + 5; i--)
            {
                if (result3.Get<byte>(i, dataArea[1] - 200) > 0)
                {
                    leftShangOrdinates[2] = i;
                    break;
                }
            }
            if (leftShangOrdinates[2] != 0)
                leftShangOrdinates[0] = dataArea[1] - 250;
            #endregion
            #region//右上
            for (int i = rightExtractionRange[0] - 50; i < result3.Rows; i++)
            {
                if (result3.Get<byte>(i, dataArea[2] + 250) > 0)
                {
                    rightShangOrdinates[1] = i;
                    break;
                }
            }
            for (int i = rightShangOrdinates[1] + 50; i > rightShangOrdinates[1] + 5; i--)
            {
                if (result3.Get<byte>(i, dataArea[2] + 200) > 0)
                {
                    rightShangOrdinates[2] = i;
                    break;
                }
            }
            if (rightShangOrdinates[2] != 0)
                rightShangOrdinates[0] = dataArea[2] + 250;
            #endregion
            maxSpacing[0] = dataArea[1] - 100;
            maxSpacing[1] = dataArea[2] + 100;
            //LineShow(gray, leftShangOrdinates[0], leftShangOrdinates[1], leftShangOrdinates[0], leftShangOrdinates[2]);
            //LineShow(gray, rightShangOrdinates[0], rightShangOrdinates[1], rightShangOrdinates[0], rightShangOrdinates[2]);
            //LineShow(gray, maxSpacing[0], leftExtractionRange[0], maxSpacing[0], leftExtractionRange[1]);
            //LineShow(gray, maxSpacing[1], rightExtractionRange[0], maxSpacing[1], rightExtractionRange[1]);
            //ImageShow(gray);
            Mat zengqiang = new Mat();
            PointEnhancement(gray, out zengqiang);
            Mat sobel2 = new Mat();
            EdgeY2(gray, out sobel2);
            //EdgeY2(zengqiang, out sobel2);
            //Sobel(zengqiang, out sobel2);
            Mat thresh2 = new Mat();
            thresh2 = sobel2.Threshold(200, 1, ThresholdTypes.Binary);
            Cv2.Rectangle(thresh2, new Rect(maxSpacing[0], 0, 1, thresh2.Rows), new Scalar(0), -1);
            Cv2.Rectangle(thresh2, new Rect(maxSpacing[1], 0, 1, thresh2.Rows), new Scalar(0), -1);
            Cv2.Rectangle(thresh2, new Rect(0, 0, thresh2.Cols, leftExtractionRange[0]), new Scalar(0), -1);
            Cv2.Rectangle(thresh2, new Rect(0, leftExtractionRange[1] + 20, thresh2.Cols, thresh2.Rows - leftExtractionRange[1] - 20), new Scalar(0), -1);
            Mat nomin2 = new Mat();
            GetArea(thresh2, out nomin2, 10, true);
            Mat result2 = nomin2.Clone();
            //ImageShow(thresh2*255, nomin2 * 255,nomin2*100+gray);

            #region//左下
            int compensate = 5;
            for (int i = leftExtractionRange[0] + 20; i < leftExtractionRange[1] - 40; i++)
            {
                sum = result2[i, i + 1, maxSpacing[0] - 10, maxSpacing[0] + 10].Sum();
                if ((int)sum > 10)
                {
                    leftXiaOrdinates[1] = i;
                    break;
                }
            }
            for (int i = leftXiaOrdinates[1] + 20; i < leftExtractionRange[1] - 20; i++)
            {
                sum = result2[i, i + 1, maxSpacing[0] - 10, maxSpacing[0] + 10].Sum();
                if ((int)sum > 10)
                {
                    leftXiaOrdinates[2] = i;
                    break;
                }
            }
            leftXiaOrdinates[0] = maxSpacing[0];
            leftXiaOrdinates[1] += compensate;
            #endregion
            #region//右下
            for (int i = rightExtractionRange[0] + 20; i < rightExtractionRange[1] - 40; i++)
            {
                sum = result2[i, i + 1, maxSpacing[1] - 10, maxSpacing[1] + 10].Sum();
                if ((int)sum > 20)
                {
                    rightXiaOrdinates[1] = i;
                    break;
                }
            }
            for (int i = rightXiaOrdinates[1] + 20; i < rightExtractionRange[1] - 20; i++)
            {
                sum = result2[i, i + 1, maxSpacing[1] - 10, maxSpacing[1] + 10].Sum();
                if ((int)sum > 10)
                {
                    rightXiaOrdinates[2] = i;
                    break;
                }
            }
            rightXiaOrdinates[0] = maxSpacing[1];
            rightXiaOrdinates[1] += compensate;
            #endregion
            #region//下层迭代
            if (leftXiaOrdinates[1] < 10 || rightXiaOrdinates[1] < 10)
            {
                int leftThresh = 200, rightThresh = 200;
                while (leftXiaOrdinates[1] < 10)
                {
                    if (leftThresh == 0)
                        break;
                    leftThresh -= 10;
                    thresh2 = sobel2.Threshold(leftThresh, 1, ThresholdTypes.Binary);
                    Cv2.Rectangle(thresh2, new Rect(maxSpacing[0], 0, 1, thresh2.Rows), new Scalar(0), -1);
                    GetArea(thresh2, out nomin2, 500, true);
                    for (int i = leftExtractionRange[0] + 20; i < leftExtractionRange[1] - 30; i++)
                    {
                        sum = nomin2[i, i + 1, maxSpacing[0] - 20, maxSpacing[0] + 20].Sum();
                        if ((int)sum > 20)
                        {
                            leftXiaOrdinates[1] = i;
                            break;
                        }
                    }
                }
                for (int i = leftXiaOrdinates[1] + 20; i < leftExtractionRange[1] - 10; i++)
                {
                    sum = result2[i, i + 1, maxSpacing[0] - 20, maxSpacing[0] + 20].Sum();
                    if ((int)sum > 20)
                    {
                        leftXiaOrdinates[2] = i;
                        break;
                    }
                }
                while (rightXiaOrdinates[1] < 10)
                {
                    if (rightThresh == 0)
                        break;
                    rightThresh -= 10;
                    thresh2 = sobel2.Threshold(rightThresh, 1, ThresholdTypes.Binary);
                    Cv2.Rectangle(thresh2, new Rect(maxSpacing[1], 0, 1, thresh2.Rows), new Scalar(0), -1);
                    GetArea(thresh2, out nomin2, 500, true);
                    for (int i = rightExtractionRange[0] + 20; i < rightExtractionRange[1] - 30; i++)
                    {
                        sum = nomin2[i, i + 1, maxSpacing[1] - 20, maxSpacing[1] + 20].Sum();
                        if ((int)sum > 20)
                        {
                            rightXiaOrdinates[1] = i;
                            break;
                        }
                    }
                }
                for (int i = rightXiaOrdinates[1] + 20; i < rightExtractionRange[1] - 10; i++)
                {
                    sum = result2[i, i + 1, maxSpacing[1] - 20, maxSpacing[1] + 20].Sum();
                    if ((int)sum > 20)
                    {
                        rightXiaOrdinates[2] = i;
                        break;
                    }
                }
            }
            if (leftXiaOrdinates[2] == 0 || rightXiaOrdinates[2] == 0)
            {

                int leftThresh = 200, rightThresh = 200;
                while (leftXiaOrdinates[2] == 0)
                {
                    if (leftThresh == 0)
                        break;
                    leftThresh -= 10;
                    thresh2 = sobel2.Threshold(leftThresh, 1, ThresholdTypes.Binary);
                    Cv2.Rectangle(thresh2, new Rect(maxSpacing[0], 0, 1, thresh2.Rows), new Scalar(0), -1);
                    GetArea(thresh2, out nomin2, 500, true);
                    for (int i = leftXiaOrdinates[1] + 20; i < leftExtractionRange[1] - 10; i++)
                    {
                        sum = nomin2[i, i + 1, maxSpacing[0] - 20, maxSpacing[0] + 20].Sum();
                        if ((int)sum > 20)
                        {
                            leftXiaOrdinates[2] = i;
                            break;
                        }
                    }
                }
                while (rightXiaOrdinates[2] == 0)
                {
                    if (rightThresh == 0)
                        break;
                    rightThresh -= 10;
                    thresh2 = sobel2.Threshold(rightThresh, 1, ThresholdTypes.Binary);
                    Cv2.Rectangle(thresh2, new Rect(maxSpacing[1], 0, 1, thresh2.Rows), new Scalar(0), -1);
                    GetArea(thresh2, out nomin2, 500, true);
                    for (int i = rightXiaOrdinates[1] + 20; i < rightExtractionRange[1] - 10; i++)
                    {
                        sum = nomin2[i, i + 1, maxSpacing[1] - 20, maxSpacing[1] + 20].Sum();
                        if ((int)sum > 20)
                        {
                            rightXiaOrdinates[2] = i;
                            break;
                        }
                    }
                }

            }
            #endregion
            //LineShow(gray, leftShangOrdinates[0], leftShangOrdinates[1], leftShangOrdinates[0], leftShangOrdinates[2]);
            //LineShow(gray, rightShangOrdinates[0], rightShangOrdinates[1], rightShangOrdinates[0], rightShangOrdinates[2]);
            //LineShow(gray, leftXiaOrdinates[0], leftXiaOrdinates[1], leftXiaOrdinates[0], leftXiaOrdinates[2]);
            //LineShow(gray, rightXiaOrdinates[0], rightXiaOrdinates[1], rightXiaOrdinates[0], rightXiaOrdinates[2]);
            //ImageShow(gray);
        }
        public void GetXigaoArea0(Mat image, out int[] dataArea, out int start)
        {
            dataArea = new int[4];
            start = 0;
            Scalar leftMax = new Scalar(0);
            Scalar rightMax = new Scalar(0);
            int thresh1 = 120, thresh2 = 200;
            for (int j = 0; j < image.Cols; j++)
            {
                leftMax = image[0, image.Rows, j, j + 1].Sum();
                if ((int)leftMax > thresh1)
                {
                    dataArea[0] = j;
                    break;
                }
            }
            for (int j = dataArea[0]; j < image.Cols; j++)
            {
                leftMax = image[0, image.Rows, j, j + 1].Sum();
                if ((int)leftMax > thresh2)
                {
                    dataArea[1] = j;
                    break;
                }
            }
            for (int j = image.Cols - 1; j > 0; j--)
            {
                rightMax = image[0, image.Rows, j - 1, j].Sum();
                if ((int)rightMax > thresh1)
                {
                    dataArea[3] = j;
                    break;
                }
            }
            for (int j = dataArea[3]; j > 0; j--)
            {
                rightMax = image[0, image.Rows, j - 1, j].Sum();
                if ((int)rightMax > thresh2)
                {
                    dataArea[2] = j;
                    break;
                }
            }
            Scalar sum = new Scalar(0);
            for (int i = 0; i < image.Rows; i++)
            {
                sum = image[i, i + 1, dataArea[0], dataArea[3]].Sum();
                if ((int)sum > 0)
                {
                    start = i;
                    break;
                }
            }

        }
        public void GetXigaoArea(Mat image, out int[] dataArea, out int start)
        {
            dataArea = new int[4];
            start = 0;
            Scalar leftMax = new Scalar(0);
            Scalar rightMax = new Scalar(0);
            int thresh1 = 140, thresh2 = 300;

            for (int j = 0; j < image.Cols; j++)
            {
                leftMax = image[0, image.Rows, j, j + 1].Sum();
                if ((int)leftMax > thresh1)
                {
                    dataArea[0] = j;
                    break;
                }
            }

            for (int j = dataArea[0]; j < image.Cols; j++)
            {
                leftMax = image[0, image.Rows, j, j + 1].Sum();
                if ((int)leftMax > thresh2)
                {
                    dataArea[1] = j;
                    break;
                }
            }

            for (int j = image.Cols - 1; j > 0; j--)
            {
                rightMax = image[0, image.Rows, j - 1, j].Sum();
                if ((int)rightMax > thresh1)
                {
                    dataArea[3] = j;
                    break;
                }
            }

            for (int j = dataArea[3]; j > 0; j--)
            {
                rightMax = image[0, image.Rows, j - 1, j].Sum();
                if ((int)rightMax > thresh2)
                {
                    dataArea[2] = j;
                    break;
                }
            }

            Scalar sum = new Scalar(0);
            for (int i = 0; i < image.Rows; i++)
            {
                sum = image[i, i + 1, dataArea[0], dataArea[3]].Sum();
                if ((int)sum > 0)
                {
                    start = i;
                    break;
                }
            }
        }
        /// <summary>
        /// 判断正向黑块是否突出
        /// </summary>
        /// <param name="image">原图</param>
        /// <param name="contour">二值图</param>
        /// <param name="tuchu">黑块是否突出，true：突出；false：不突出；</param>
        /// <param name="dataArea">提取区域</param>
        /// <param name="start">上像素边界</param>
        /// <param name="Hang"></param>
        public void HeiKuai(Mat image, Mat contour, out bool tuchu, int[] dataArea, int start, out int[] Hang)
        {
            tuchu = new bool();
            Scalar sum = new Scalar(0);
            Hang = new int[4];

            Mat imageBlur = new Mat();
            Cv2.GaussianBlur(image, imageBlur, new Size(11, 11), 5, 5);//模糊
            int minThresh = 18;
            int maxThresh = 20;
            Mat edge = new Mat();
            Cv2.Canny(imageBlur, edge, minThresh, maxThresh);//边缘检测

            ////闭运算
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Mat close = new Mat();
            Cv2.MorphologyEx(edge, edge, MorphTypes.Close, se);
            //new Window("edge", WindowMode.Normal, edge * 255);

            //左侧
            for (int i = start; i < edge.Rows; i++)//求左边缘检测图行
            {
                sum = edge[i, i + 1, 500, dataArea[1] - 50].Sum();
                if ((int)sum > 255)
                {
                    Hang[0] = i;
                    break;
                }
            }

            for (int i = start; i < contour.Rows; i++)//求左二值图行
            {
                sum = contour[i, i + 1, 500, dataArea[1] - 50].Sum();
                if ((int)sum > 5)
                {
                    Hang[1] = i;
                    break;
                }
            }

            for (int i = start; i < edge.Rows; i++)//求右边缘检测图行
            {
                sum = edge[i, i + 1, dataArea[2] + 50, dataArea[3] - 200].Sum();
                if ((int)sum > 255)
                {
                    Hang[2] = i;
                    break;
                }
            }

            for (int i = start; i < contour.Rows; i++)//求右二值图行
            {
                sum = contour[i, i + 1, dataArea[2] + 50, dataArea[3] - 200].Sum();
                if ((int)sum > 5)
                {
                    Hang[3] = i;
                    break;
                }
            }





            if (Hang[1] - Hang[0] > 20 & Hang[3] - Hang[2] > 20)
            {
                tuchu = true;
            }
            else
            {
                tuchu = false;
            }
        }
        public void Heikuai2(Mat gray, int start, int[] dataArea, out bool tuchu)
        {
            tuchu = false;
            #region//測試
            //Mat thresh4 = new Mat();
            //double t3 = Cv2.Threshold(gray, thresh4, 0, 1, ThresholdTypes.Otsu);
            //Mat sobel4 = new Mat();
            //Sobel(thresh4, out sobel4);
            //Mat zengqiang2 = new Mat();
            //Cv2.EqualizeHist(gray, zengqiang2);
            ////ceju.ImageShow(sobel2 * 255);
            //CvTrackbarCallback cvTrackbarCallback = new CvTrackbarCallback(Text);
            //Window window = new Window("tbar", WindowMode.Normal);//创建一个新窗口"tbar"
            //CvTrackbar cvTrackbarV = new CvTrackbar("bar1", "tbar", 100, 255, cvTrackbarCallback);

            //Cv2.WaitKey();
            //void Text(int value)
            //{
            //    //thresh4 = gray.Threshold(t3 - value, 1, ThresholdTypes.Binary);
            //    //sobel4 = new Mat();
            //    //ceju.Sobel(thresh4, out sobel4);
            //    //new Window("tbar", WindowMode.Normal, sobel4 * 255);

            //    //EdgeY(zengqiang2, out sobel4);
            //    Sobel(gray, out sobel4);
            //    thresh4 = sobel4.Threshold(value, 1, ThresholdTypes.Binary);
            //    new Window("tbar", WindowMode.Normal, thresh4 * 255);
            //}
            #endregion
            Scalar sum = new Scalar();
            Mat thresh2 = new Mat();
            double t = Cv2.Threshold(gray, thresh2, 0, 1, ThresholdTypes.Otsu);
            thresh2 = gray.Threshold(t - 30, 1, ThresholdTypes.Binary);
            Mat sobel2 = new Mat();
            Sobel(thresh2, out sobel2);
            Mat result2 = sobel2.Clone();
            int leftStart = 0;
            for (int i = start - 300; i < result2.Rows; i++)
            {
                sum = result2[i, i + 1, dataArea[0], dataArea[1]].Sum();
                if ((int)sum > 50)
                {
                    leftStart = i;
                    break;
                }
            }

            Mat sobel = new Mat();
            Sobel(gray, out sobel);
            Mat thresh = new Mat();
            thresh = sobel.Threshold(10, 1, ThresholdTypes.Binary);
            Cv2.Rectangle(thresh, new Rect(dataArea[1] - 50, 0, thresh.Cols - dataArea[1] + 100, thresh.Rows), new Scalar(0), -1);
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
            Mat close = new Mat();
            Cv2.MorphologyEx(thresh, close, MorphTypes.Close, seClose);
            //ImageShow(close * 255);
            Mat nomin = new Mat();
            GetArea(close, out nomin, 100, true);
            Mat result1 = nomin.Clone();
            //ImageShow(nomin * 255);
            int heixian = 0;
            for (int i = start + 300; i < leftStart; i++)
            {
                sum = result1[i, i + 1, dataArea[0], dataArea[1]].Sum();
                if ((int)sum > 30)
                {
                    heixian = i;
                    break;
                }
            }
            //LineShow(gray, 0, leftStart, gray.Cols, leftStart);
            //LineShow(gray, 0, heixian, gray.Cols, heixian);
            //ImageShow(gray);
            if ((leftStart - heixian) > 30 && heixian != 0)
                tuchu = true;


        }
        public void Heikuai3(Mat gray, int start, int[] dataArea, out bool tuchu)
        {
            tuchu = false;
            Mat thresh = new Mat();
            double t = Cv2.Threshold(gray, thresh, 0, 1, ThresholdTypes.Otsu);
            thresh = gray.Threshold(t - 30, 1, ThresholdTypes.Binary);
            Mat result1 = thresh.Clone();

            Mat sobel = new Mat();
            Sobel(gray, out sobel);
            Mat threshSobel = new Mat();
            threshSobel = sobel.Threshold(10, 1, ThresholdTypes.Binary);
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Mat open = new Mat();
            Cv2.MorphologyEx(threshSobel, open, MorphTypes.Open, seOpen);
            //Mat nomin = new Mat();
            //GetArea(open, out nomin, 500, true);
            Mat result2 = open.Clone();

            //ImageShow(result2 * 255);
            int leftStart = 0;
            Scalar sum = new Scalar(0);
            for (int i = start + 300; i < result1.Rows; i++)
            {
                sum = result1[i, i + 1, dataArea[0], dataArea[1] - 100].Sum();
                if ((int)sum > 20)
                {
                    leftStart = i;
                    break;
                }
            }
            //LineShow(gray, dataArea[1] - 400, leftStart - 100, dataArea[1] - 100, leftStart - 10);
            //ImageShow(gray, result2 * 255,result1*255);
            int leftBlackBorder = 0;
            for (int j = dataArea[1] - 400; j < dataArea[1] - 100; j++)
            {
                sum = result2[leftStart - 100, leftStart - 10, j, j + 1].Sum();
                if ((int)sum > 20)
                {
                    leftBlackBorder = j;
                    break;
                }
            }
            if (leftBlackBorder != 0)
                tuchu = true;
        }
        //判断是否弯曲
        public void WanQu(Mat contour, out bool wanQu, int[] dataArea, int start, out int[] a)
        {
            a = new int[3];
            wanQu = new bool();
            //int max=new int();
            for (int i = start; i < contour.Rows; i++)
            {
                if (contour.Get<byte>(i, dataArea[1] - 150) > 0)
                {
                    a[0] = i;
                    break;
                }
            }
            for (int i = start; i < contour.Rows; i++)
            {
                if (contour.Get<byte>(i, dataArea[1] - 50) > 0)
                {
                    a[1] = i;
                    break;
                }
            }
            //int[] zongzuobiao = new int[150 - 51];
            int[] zongzuobiao = new int[dataArea[1] - dataArea[0] - 200];
            int count = 0;
            //for (int j = dataArea[1] - 149; j < dataArea[1] - 51; j++)
            for (int j = dataArea[0] + 100; j < dataArea[1] - 100; j++)
            {
                for (int i = start; i < contour.Rows; i++)
                {
                    if (contour.Get<byte>(i, j) > 0)
                    {
                        zongzuobiao[count] = i;
                        count++;
                        break;
                    }
                }
            }
            int max = zongzuobiao.Max();
            int min = zongzuobiao.Min();
            int idxMax = 0, idxMin = 0;
            for (int i = 0; i < zongzuobiao.Length; i++)
            {
                if (zongzuobiao[i] == max)
                    idxMax = i;
                if (zongzuobiao[i] == min)
                    idxMin = i;
            }
            //判断是否在中间
            if (idxMax > zongzuobiao.Length / 3 && idxMax < zongzuobiao.Length / 3 * 2)
            {
                wanQu = false;
            }


            else
            {
                wanQu = true;
            }
        }
        public void WanQu2(Mat gray, out bool wanQu, int[] dataArea, int start, out int[] a)
        {
            a = new int[3];
            wanQu = false;
            int leftStart = 0;
            Mat thresh = new Mat();
            double t = Cv2.Threshold(gray, thresh, 0, 1, ThresholdTypes.Otsu);
            thresh = gray.Threshold(t - 30, 1, ThresholdTypes.Binary);
            for (int i = start + 300; i < thresh.Rows; i++)
            {
                if (thresh.Get<byte>(i, dataArea[1] + 50) > 0)
                {
                    leftStart = i;
                    break;
                }
            }
            Scalar sum = new Scalar();
            for (int i = start + 300; i < leftStart; i++)
            {
                sum = thresh[i, i + 1, dataArea[1] - 200, dataArea[1] - 100].Sum();
                if ((int)sum > 0)
                {
                    wanQu = true;
                }
            }
            //LineShow(gray, dataArea[1] + 50, leftStart, dataArea[1] + 50, start);
            //ImageShow(gray,thresh*255);
        }
        public void youCexiangsu(Mat contour, out bool cunzai, out int lowrow, out int[] zuidalie, int[] dataArea)
        {
            cunzai = new bool();
            zuidalie = new int[2];
            lowrow = new int();

            //左最大列
            Scalar max = new Scalar(0);
            for (int j = 0; j < contour.Cols / 2; j++)
            {
                Scalar sum = new Scalar(0);
                sum = contour[0, contour.Rows, j, j + 1].Sum();
                if ((int)sum > (int)max)
                {
                    max = sum;
                    zuidalie[0] = j;
                }
            }
            ////右最大列
            //Scalar max1 = new Scalar(0);
            //for (int j = contour.Cols; j > contour.Cols / 2; j--)
            //{
            //    Scalar sum = new Scalar(0);
            //    sum = contour[0, contour.Rows, j-1, j].Sum();
            //    if ((int)sum > (int)max1)
            //    {
            //        max1 = sum;
            //        zuidalie[1] = j;
            //    }
            //}

            //左底行
            for (int i = 0; i < contour.Rows; i++)
            {
                if (contour.Get<byte>(i, dataArea[1] - 150) > 0)
                {
                    lowrow = i;
                    break;
                }
            }
            Scalar sum1 = new Scalar(0);
            sum1 = contour[0, lowrow - 150, zuidalie[0] + 100, zuidalie[0] + 101].Sum();
            //Console.WriteLine(sum1);
            if ((int)sum1 > 0)
            {
                cunzai = true;
            }
            else
            {
                cunzai = false;
            }
        }
        /// <summary>
        /// 计算锡膏的上层坐标
        /// </summary>
        /// <param name="contour">二值图</param>
        /// <param name="filter">红色通道增强后图</param>
        /// <param name="leftShang">左边上层坐标，0:横坐标；1：上纵坐标；2：下纵坐标</param>
        /// <param name="rightShang">右边上层坐标，0:横坐标；1：上纵坐标；2：下纵坐标</param>
        /// <param name="upperBorder">上界</param>
        /// <param name="dataArea">数据提取区域</param>
        public void Shang(Mat contour, Mat filter, out int[] leftShang, out int[] rightShang, int upperBorder, int[] dataArea)
        {
            leftShang = new int[3];//0:横坐标；1：上纵坐标；2：下纵坐标
            rightShang = new int[3];
            Scalar sum = new Scalar(0);
            //左侧
            for (int i = upperBorder; i < contour.Rows; i++)//求上纵坐标
            {
                sum = contour[i, i + 1, dataArea[0], dataArea[1] - 50].Sum();
                if ((int)sum > 0)
                {
                    leftShang[1] = i;
                    break;
                }
            }
            for (int j = dataArea[1] - 50; j > dataArea[0]; j--)//求横坐标
            {
                if (contour.Get<byte>(leftShang[1], j) > 0)
                {
                    leftShang[0] = j;
                    break;
                }
            }
            Mat cropLeft = filter[leftShang[1] + 2, leftShang[1] + 20, leftShang[0] - 1, leftShang[0] + 1].Clone();
            Mat threshLeft = cropLeft.Threshold(0, 1, ThresholdTypes.Otsu);
            for (int i = 0; i < threshLeft.Rows; i++)//求下纵坐标
            {
                sum = threshLeft[i, i + 1, 0, threshLeft.Cols].Sum();
                if ((int)sum == 0)
                {
                    leftShang[2] = i + leftShang[1] + 2;
                    break;
                }
            }
            //右侧
            for (int i = upperBorder; i < contour.Rows; i++)//求上纵坐标
            {
                sum = contour[i, i + 1, dataArea[2] + 50, dataArea[3]].Sum();
                if ((int)sum > 0)
                {
                    rightShang[1] = i;
                    break;
                }
            }
            for (int j = dataArea[2] + 50; j < dataArea[3]; j++)//求横坐标
            {
                if (contour.Get<byte>(rightShang[1], j) > 0)
                {
                    rightShang[0] = j;
                    break;
                }
            }
            Mat cropRight = filter[rightShang[1] + 2, rightShang[1] + 20, rightShang[0] - 1, rightShang[0] + 1].Clone();
            Mat threshRight = cropRight.Threshold(0, 1, ThresholdTypes.Otsu);
            for (int i = 0; i < threshRight.Rows; i++)//求下纵坐标
            {
                sum = threshRight[i, i + 1, 0, threshRight.Cols].Sum();
                if ((int)sum == 0)
                {
                    rightShang[2] = i + rightShang[1] + 2;
                    break;
                }
            }
        }
        /// <summary>
        /// 计算锡膏下层坐标
        /// </summary>
        /// <param name="image">原图</param>
        /// <param name="contour">二值图</param>
        /// <param name="leftXia">左边坐标，0：横坐标；1：上纵坐标；2：下纵坐标</param>
        /// <param name="rightXia">右边坐标，0：横坐标；1：上纵坐标；2：下纵坐标</param>
        /// <param name="dataArea">提取区域</param>
        /// <param name="leftUpper">左边上层，leftShangOrdinate[1]</param>
        /// <param name="rightUpper">右边上层，rightShangOrdinate[1]</param>
        public void Xia(Mat image, Mat contour, out int[] leftXia, out int[] rightXia, int[] dataArea, int leftUpper, int rightUpper)
        {
            leftXia = new int[3];
            rightXia = new int[3];
            //leftXia[0] = dataArea[1] - 50;
            //rightXia[0] = dataArea[2] + 50;  
            //找下界
            Scalar sum = new Scalar(0);
            int leftLower = 0, rightLower = 0;
            for (int i = leftUpper; i < contour.Rows; i++)
            {
                sum = contour[i, i + 1, dataArea[0], dataArea[1]].Sum();
                if ((int)sum == 0)
                {
                    leftLower = i;
                    break;
                }
            }
            for (int i = rightUpper; i < contour.Rows; i++)
            {
                sum = contour[i, i + 1, dataArea[2], dataArea[3]].Sum();
                if ((int)sum == 0)
                {
                    rightLower = i;
                    break;
                }
            }
            //找到中间画线处，局部最大值
            int rangeInside = 30;
            int rangeOutside = 100;
            Scalar max = new Scalar(0);
            for (int j = dataArea[0] + rangeOutside; j < dataArea[1] - rangeInside; j++)
            {
                sum = contour[leftUpper + 20, leftLower - 5, j, j + 50].Sum();
                if ((int)sum > (int)max)
                {
                    leftXia[0] = j + 25;
                    max = sum;
                }
            }
            max = 0;
            for (int j = dataArea[2] + rangeInside; j < dataArea[3] - rangeInside; j++)
            {
                sum = contour[rightUpper + 20, rightLower - 5, j, j + 50].Sum();
                if ((int)sum > (int)max)
                {
                    max = sum;
                    rightXia[0] = j + 25;
                }
            }
            //边缘检测
            int minThresh = 30;
            int maxThresh = 55;
            Mat edge = new Mat();
            Cv2.Canny(image, edge, minThresh, maxThresh);


            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Mat close = new Mat();
            Cv2.MorphologyEx(edge, close, MorphTypes.Close, se);
            Mat se2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 1));
            Mat erode = new Mat();
            Cv2.Erode(close, erode, se2);
            //ImageShow(edge,close,erode);
            erode = erode / 255;
            //计算高度
            for (int i = leftUpper + 20; i < leftLower - 5; i++)//左边坐标上层
            {
                sum = erode[i, i + 1, leftXia[0] - 10, leftXia[0] + 10].Sum();
                if ((int)sum > 5)
                {
                    leftXia[1] = i;
                    break;
                }
            }
            for (int i = leftXia[1] + 10; i < leftLower - 5; i++)//左边坐标下层
            {
                sum = erode[i, i + 1, leftXia[0] - 10, leftXia[0] + 10].Sum();
                if ((int)sum > 10)
                {
                    leftXia[2] = i;
                    break;
                }
            }
            for (int i = rightUpper + 20; i < rightLower - 5; i++)//右边坐标上层
            {
                sum = erode[i, i + 1, rightXia[0] - 10, rightXia[0] + 10].Sum();
                if ((int)sum > 10)
                {
                    rightXia[1] = i;
                    break;
                }
            }
            for (int i = rightXia[1] + 10; i < rightLower - 5; i++)//右边坐标下层
            {
                sum = erode[i, i + 1, rightXia[0] - 10, rightXia[0] + 10].Sum();
                if ((int)sum > 5)
                {
                    rightXia[2] = i;
                    break;
                }
            }
            //Mat cropLeft = erode[leftUpper + 20, leftLower - 5, leftXia[0] - 10, leftXia[0] + 10].Clone();
            //Mat cropRight = erode[rightUpper + 20, rightLower - 5, rightXia[0] - 10, rightXia[0] + 10].Clone();
            //ImageShow(cropLeft, cropRight);



            //CvTrackbarCallback cvTrackbarCallback = new CvTrackbarCallback(Text);
            //CvTrackbarCallback cvTrackbarCallback2 = new CvTrackbarCallback(Text2);
            //Window window = new Window("tbar");//创建一个新窗口"tbar"
            //CvTrackbar cvTrackbarV = new CvTrackbar("bar1", "tbar", 20, 100, cvTrackbarCallback);
            //CvTrackbar cvTrackbar2 = new CvTrackbar("bar2", "tbar", 50, 100, cvTrackbarCallback2);
            //Cv2.WaitKey();

            //LineShow(image, leftXia[0], leftXia[1], leftXia[0], leftXia[2]);
            //LineShow(image, rightXia[0], rightXia[1], rightXia[0], rightXia[2]);
            //ImageShow(image);
            //ImageShow(threshLeft, threshRight);
            //ImageShow(sobelLeft, sobelRight);

            //void  Text(int value)
            //{
            //    minThresh = value;
            //    Cv2.Canny(image, edge, minThresh, maxThresh);
            //    new Window("tbar", edge);
            //}
            //void Text2(int value)
            //{
            //    maxThresh = value;
            //    Cv2.Canny(image, edge, minThresh, maxThresh);
            //    new Window("tbar", edge);
            //}
        }

        /// <summary>
        /// 锡膏z 上面测量线的 精确计算
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        /// <param name="tonghouY"></param>
        /// <param name="fanghanhouduY"></param>
        /// <param name="a"></param>
        public void Xigaozhoudu_ACC_upLines(Mat gray0, out int xigaohouduY1, out int xigaohouduY2, out int existOneTwoPoint, out int xigaoTopY)
        {
            xigaohouduY1 = 0;// 30;
            xigaohouduY2 = 40;
            xigaoTopY = 0;
            existOneTwoPoint = 0;
            {
                int minGray = 300 * 255;
                int minRowIndex = 0; int minRowInStart = 0; int colEnd = gray0.Cols - 1; int curGray; List<int> curGrayList = new List<int>();
                xigaohouduY1 = 15;// 10;
                for (int i = Math.Min(55/*65*//*55*/, gray0.Rows) - 5; i > xigaohouduY1; i--)
                {
                    curGray = this.XigaohouduForAreaMin(gray0, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                    curGrayList.Insert(0, curGray);
                    if (curGray < minGray)
                    {
                        minRowIndex = i;
                        minGray = curGray;
                    }
                    else if (curGray - minGray > 100/*400*//*参数调试-阈值*/)
                    {
                        minRowInStart = i;
                        break;
                    }
                }
                if (minRowIndex < 30)//继续往下多走10个像素
                {
                    minRowInStart = 0; curGrayList.Clear(); minGray = 300 * 255;
                    for (int i = Math.Min(65/*55*/, gray0.Rows) - 5; i > xigaohouduY1; i--)
                    {
                        curGray = this.XigaohouduForAreaMin(gray0, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                        curGrayList.Insert(0, curGray);
                        if (curGray < minGray)
                        {
                            minRowIndex = i;
                            minGray = curGray;
                        }
                        else if (curGray - minGray > 400/*100*//*400*//*参数调试-阈值*/)
                        {
                            minRowInStart = i;
                            break;
                        }
                    }
                }
                if (minRowIndex < 30 && minRowInStart > 5)//继续往上走找上端点用于最后的优化，以便找到模糊的
                {
                    List<int> upGrays = new List<int>(); int upMinG = 300 * 255;
                    for (int i = minRowIndex - 5; i > 5; i--)
                    {
                        curGray = this.XigaohouduForAreaMin(gray0, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                        upGrays.Insert(0, curGray);
                        if (curGray < minGray)
                        {
                            xigaoTopY = i;
                            break;
                        }
                        //if (curGray < minGray)
                        //{
                        //    minRowIndex = i;
                        //    minGray = curGray;
                        //}
                        //else if (curGray - minGray > 400/*100*//*400*//*参数调试-阈值*/)
                        //{
                        //    minRowInStart = i;
                        //    break;
                        //}
                    }
                    upMinG = upGrays.Min();
                }
                List<int> upGrayList = new List<int>();
                for (int i = 0; i < minRowIndex; i ++)
                {
                    curGray = this.XigaohouduForAreaMin(gray0, i);
                    upGrayList.Add(curGray);
                }
                xigaohouduY2 = minRowIndex;
                if (xigaohouduY2 > 30)
                {
                    existOneTwoPoint = 1;
                }
            }
            if (false)
            {
                int minGray = 300 * 255;
                int minRowIndex = 0; int colEnd = gray0.Cols - 1; int curGray; List<int> curGrayList = new List<int>();
                xigaohouduY1 = 10;
                for (int i = xigaohouduY1; i < Math.Min(50, gray0.Rows) - 5; i++)
                {
                    int v = gray0.Row[i].CountNonZero();
                    if (v > colEnd / 2)
                    {
                        xigaohouduY1 = i;
                        break;
                    }
                }
                if (xigaohouduY1 < 36)
                {
                    for (int i = xigaohouduY1 + 5/*10*//*5*/; i < Math.Min(55, gray0.Rows) - 5; i++)
                    {
                        curGray = this.XigaohouduForAreaMin(gray0, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                        curGrayList.Add(curGray);
                        if (curGray < minGray)
                        {
                            minRowIndex = i;
                            minGray = curGray;
                        }
                    }
                    for (int i = (minRowIndex - xigaohouduY1 - 5/*10*/) + 2; i < curGrayList.Count; i += 2)
                    {
                        if (Math.Abs(curGrayList[i] - minGray) < 10/*100*/)
                        {
                            minRowIndex += 1;
                        }
                        else
                            break;
                    }
                }
                else
                    minRowIndex = xigaohouduY1 + 1;
                xigaohouduY2 = minRowIndex;// 84;// 72;// minRowIndex;
            }
            Console.WriteLine("noSharp：" + xigaohouduY2 + ";xigaohouduY1:" + xigaohouduY1 + "...");
        }

        /// <summary>
        /// 锡膏z 上面测量线的 精确计算
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        /// <param name="tonghouY"></param>
        /// <param name="fanghanhouduY"></param>
        /// <param name="a"></param>
        public void Xigaozhoudu_ACC_upLines__0(Mat gray0, out int xigaohouduY1, out int xigaohouduY2)
        {
            xigaohouduY1 = 30;
            xigaohouduY2 = 40;
            {
                int minGray = 300 * 255;
                int minRowIndex = 0; int colEnd = gray0.Cols - 1; int curGray; List<int> curGrayList = new List<int>();
                xigaohouduY1 = 10;
                for (int i = xigaohouduY1; i < Math.Min(50, gray0.Rows) - 5; i++)
                {
                    int v = gray0.Row[i].CountNonZero();
                    if (v > colEnd / 2)
                    {
                        xigaohouduY1 = i;
                        break;
                    }
                }
                if (xigaohouduY1 < 36)
                {
                    for (int i = xigaohouduY1 + 5/*10*//*5*/; i < Math.Min(55, gray0.Rows) - 5; i++)
                    {
                        curGray = this.XigaohouduForAreaMin(gray0, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                        curGrayList.Add(curGray);
                        if (curGray < minGray)
                        {
                            minRowIndex = i;
                            minGray = curGray;
                        }
                    }
                    for (int i = (minRowIndex - xigaohouduY1 - 5/*10*/) + 2; i < curGrayList.Count; i += 2)
                    {
                        if (Math.Abs(curGrayList[i] - minGray) < 10/*100*/)
                        {
                            minRowIndex += 1;
                        }
                        else
                            break;
                    }
                }
                else
                    minRowIndex = xigaohouduY1 + 1;
                xigaohouduY2 = minRowIndex;// 84;// 72;// minRowIndex;
            }
            Console.WriteLine("noSharp：" + xigaohouduY2 + ";xigaohouduY1:" + xigaohouduY1 + "...");
        }
        //获取当前行附件最暗的总和
        private int XigaohouduForAreaMin(Mat gray, int rowIndex)
        {
            int areaMin = 0;
            for (int i = 0; i < gray.Cols; i++)
            {
                int colMin = 255;
                for (int j = rowIndex - 0/*1*//*Math.Max(0, rowIndex - 5)*/; j < rowIndex + 1; j++)
                    if (gray.At<byte>(j, i) < colMin) colMin = gray.At<byte>(j, i);
                areaMin += colMin;
            }
            return areaMin;
        }


        /// <summary>
        /// 锡膏z 有开口 厚度 精确计算
        /// </summary>
        /// <param name="gray"></param>
        /// <param name="y"></param>
        /// <param name="b"></param>
        /// <param name="tonghouY"></param>
        /// <param name="fanghanhouduY"></param>
        /// <param name="a"></param>
        public void Xigaozhoudu_ACC(Mat gray0, int fanghanhouduY1__0, out int fanghanhouduY1, out int fanghanhouduY1Bottom, out int minGray, out bool skipUpLine, int a = 0)
        {
            int bottomYDistance = 20;// 25;// 15;// 30;
            int fanghanhouduY1__noSharp = -1;// fanghanhouduY1;
            skipUpLine = false;
            {
                minGray = 300 * 255;
                int minRowIndex = 0; int colEnd = gray0.Cols - 1; int curGray; List<int> curGrayList = new List<int>();
                fanghanhouduY1Bottom = 0;
                for (int i = Math.Max(0, fanghanhouduY1__0 - 4/*1*//*4*//*19*//*1*//*5*//*10*/); i < Math.Min(fanghanhouduY1__0 + bottomYDistance/*25*/, gray0.Rows) - 5; i++)
                {
                    curGray = this.FanghanhouduForAreaMin(gray0, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                    curGrayList.Add(curGray);
                    if (curGray < minGray)
                    {
                        minRowIndex = i;
                        fanghanhouduY1Bottom = i;
                        minGray = curGray;
                    }
                }
                while (minRowIndex <= 6 && minRowIndex > 1)
                {
                    curGray = this.FanghanhouduForAreaMin(gray0, minRowIndex - 1);
                    if (curGray < minGray || Math.Abs(curGray - minGray) < 10) minRowIndex -= 1;
                    else break;
                }
                for (int i = Math.Max(0, minRowIndex - Math.Max(0, fanghanhouduY1__0 - 4)) + 2; i < curGrayList.Count; i += 2)
                {
                    if (Math.Abs(curGrayList[i] - minGray) < 10/*100*/)
                    {
                        minRowIndex += 1;
                        fanghanhouduY1Bottom += 2;
                    }
                    else
                        break;
                }
                fanghanhouduY1__noSharp = minRowIndex;// 84;// 72;// minRowIndex;
            }
            {
                minGray = 300 * 255;
                //锐化
                //Mat left_small_sharp = BinaryTools.BlurMaskFunction(left_small).CvtColor(ColorConversionCodes.BGRA2GRAY);
                Mat gray = BinaryTools.BlurMaskFunction(gray0.Clone()/*grayRect*/, 4f * 3.14f, 1, 10f).CvtColor(ColorConversionCodes.BGRA2GRAY);

                //Cv2.ImWrite(@"C:\Users\win10SSD\Desktop\BlurMask" + a + "_.jpg", gray);

                int minRowIndex = 0; int colEnd = gray.Cols - 1; int curGray; List<int> curGrayList = new List<int>();
                fanghanhouduY1Bottom = 0;
                for (int i = Math.Max(0, fanghanhouduY1__0 - 4/*1*//*4*//*19*//*1*//*5*//*10*/); i < Math.Min(fanghanhouduY1__0 + bottomYDistance/*25*/, gray.Rows) - 5; i++)
                {
                    curGray = this.FanghanhouduForAreaMin(gray, i);// (int)thresh[i - 1, i, 0, colEnd].Sum().Val0;
                    curGrayList.Add(curGray);
                    if (curGray < minGray)
                    {
                        minRowIndex = i;
                        fanghanhouduY1Bottom = i;
                        minGray = curGray;
                    }
                }
                while (minRowIndex <= 6 && minRowIndex > 1)
                {
                    curGray = this.FanghanhouduForAreaMin(gray0, minRowIndex - 1);
                    if (curGray < minGray || Math.Abs(curGray - minGray) < 10) minRowIndex -= 1;
                    else break;
                }
                for (int i = Math.Max(0, minRowIndex - Math.Max(0, fanghanhouduY1__0 - 4)) + 2; i < curGrayList.Count; i += 2)
                {
                    if (Math.Abs(curGrayList[i] - minGray) < 10/*100*/)
                    {
                        minRowIndex += 1;
                        fanghanhouduY1Bottom += 2;
                    }
                    else
                        break;
                }
                //Console.WriteLine("fanghanhouduY1_1:" + minRowIndex);
                ////Cv2.ImWrite(@"C:\Users\54434\Desktop\thres_3.png", gray);
                fanghanhouduY1 = minRowIndex;// 84;// 72;// minRowIndex;
            }
            Console.Write("noSharp：" + fanghanhouduY1__noSharp + ";fanghanhouduY1:" + fanghanhouduY1 + "...");
            if (fanghanhouduY1__noSharp < 8 && fanghanhouduY1 < 8 || fanghanhouduY1__noSharp == 1 && fanghanhouduY1 > 10)
            {
                skipUpLine = true;// false;// true;
            }
            if (Math.Abs(fanghanhouduY1__noSharp - fanghanhouduY1) < 7/* <<7 8*//* << 6 *//*5*/
                || (fanghanhouduY1__noSharp - fanghanhouduY1 </*>*/ 0 && fanghanhouduY1__noSharp - fanghanhouduY1 >/*<*/ -10/*20*/))
            {
                fanghanhouduY1 = fanghanhouduY1__noSharp;
            }
            else
                Console.WriteLine("fanghanhouduY1 far away from fanghanhouduY1__noSharp.");
        }

        //锡膏Z
        /// <summary>
        /// 得到锡膏Z的数据提取区域
        /// </summary>
        /// <param name="contour"></param>
        /// <param name="imageRed"></param>
        /// <param name="dataArea"></param>
        public void GetXigaoZArea(Mat contour, Mat imageRed, out Mat resulet, out int[] dataArea, out int upperBorder, out int lowerBorder)
        {
            resulet = new Mat();
            //闭运算
            Mat close = new Mat();
            Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(27, 27));
            Cv2.MorphologyEx(contour, close, MorphTypes.Open, seClose);
            if ((int)close.Sum() < 200000)
            {
                seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
                Cv2.MorphologyEx(contour, close, MorphTypes.Open, seClose);
            }
            contour = close;
            //将中间目标区域通过掩膜弄出来
            int leftBorder = 0, rightBorder = 0;
            upperBorder = 0; lowerBorder = 0;
            Scalar sum = new Scalar(0);
            for (int i = 0; i < contour.Rows; i++)
            {
                sum = contour[i, i + 1, 0, contour.Cols].Sum();
                if ((int)sum > 200)
                {
                    upperBorder = i - 20;
                    break;
                }
            }
            for (int i = upperBorder + 100; i < contour.Rows; i++)
            {
                sum = contour[i, i + 1, 0, contour.Cols].Sum();
                if ((int)sum < 200)
                {
                    lowerBorder = i;
                    break;
                }
            }
            contour = imageRed.Threshold(0, 1, ThresholdTypes.Otsu);
            Mat delete = contour.Clone();
            Cv2.Rectangle(delete, new Rect(0, upperBorder, contour.Cols, lowerBorder - upperBorder), new Scalar(0), -1);
            contour = contour - delete;
            Mat seOpen = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Cv2.MorphologyEx(contour, contour, MorphTypes.Open, seOpen);
            resulet = contour.Clone();
            //选出两个目标的提取区域
            dataArea = new int[4];
            int middle = contour.Cols / 2;
            sum = contour[0, contour.Rows, middle, middle + 1].Sum();
            if ((int)sum > 0)
            {
                for (int j = middle; j > 0; j--)
                {
                    sum = contour[0, contour.Rows, j - 1, j].Sum();
                    if ((int)sum == 0)
                    {
                        dataArea[1] = j;
                        break;
                    }
                }
                for (int j = middle; j < contour.Cols; j++)
                {
                    sum = contour[0, contour.Rows, j, j + 1].Sum();
                    if ((int)sum == 0)
                    {
                        dataArea[1] = j;
                        break;
                    }
                }
                for (int j = dataArea[1] + 10; j < contour.Cols; j++)
                {
                    sum = contour[0, contour.Rows, j, j + 1].Sum();
                    if ((int)sum > 0)
                    {
                        dataArea[2] = j;
                        break;
                    }
                }
                for (int j = dataArea[2] + 10; j < contour.Cols; j++)
                {
                    sum = contour[0, contour.Rows, j, j + 1].Sum();
                    if ((int)sum == 0)
                    {
                        dataArea[3] = j;
                        break;
                    }
                }
            }
            else
            {
                for (int j = middle; j < contour.Cols; j++)
                {
                    sum = contour[0, contour.Rows, j, j + 1].Sum();
                    if ((int)sum > 0)
                    {
                        dataArea[0] = j;
                        break;
                    }
                }
                for (int j = dataArea[0] + 10; j < contour.Cols; j++)
                {
                    sum = contour[0, contour.Rows, j, j + 1].Sum();
                    if ((int)sum == 0)
                    {
                        dataArea[1] = j;
                        break;
                    }
                }
                for (int j = dataArea[1] + 10; j < contour.Cols; j++)
                {
                    sum = contour[0, contour.Rows, j, j + 1].Sum();
                    if ((int)sum > 0)
                    {
                        dataArea[2] = j;
                        break;
                    }
                }
                for (int j = dataArea[2] + 10; j < contour.Cols; j++)
                {
                    sum = contour[0, contour.Rows, j, j + 1].Sum();
                    if ((int)sum == 0)
                    {
                        dataArea[3] = j;
                        break;
                    }
                }
            }
        }
        /// <summary>
        /// 得到所求的坐标
        /// </summary>
        /// <param name="image"></param>
        /// <param name="contour"></param>
        /// <param name="leftOrdinate">0：横坐标；1：上纵坐标；2：下纵坐标</param>
        /// <param name="rightOrdinate">0：横坐标；1：上纵坐标；2：下纵坐标</param>
        /// <param name="upperBorder"></param>
        /// <param name="lowerBorder"></param>
        /// <param name="dataArea"></param>
        public void GetXigaoZOrdinate(Mat image, Mat contour, out int[] leftOrdinate, out int[] rightOrdinate, int upperBorder, int lowerBorder, int[] dataArea)
        {
            //边缘检测
            //ceju.ImageShow(image);
            LineEnhancement(image, out image);
            //ceju.ImageShow(image);
            Cv2.GaussianBlur(image, image, new Size(9, 9), 3, 3);
            Mat edge = new Mat();
            Cv2.Canny(image, edge, 20, 25);
            edge = edge / 255;
            //ceju.ImageShow(edge * 255);
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 1));
            Cv2.MorphologyEx(edge, edge, MorphTypes.Close, se);

            //每个目标的第一条线
            int leftFirstLine = 0, rightFirstLine = 0;
            Scalar sum = new Scalar(0);
            for (int i = upperBorder; i < lowerBorder; i++)
            {
                sum = contour[i, i + 1, dataArea[0], dataArea[1]].Sum();
                if ((int)sum > 0)
                {
                    leftFirstLine = i; break;
                }
            }
            for (int i = upperBorder; i < lowerBorder; i++)
            {
                sum = contour[i, i + 1, dataArea[2], dataArea[3]].Sum();
                if ((int)sum > 0)
                {
                    rightFirstLine = i; break;
                }
            }
            //通过最大值找出测距点
            int leftPoint = 0, rightPoint = 0;
            Scalar max = new Scalar(0);
            int middle1 = (dataArea[0] + dataArea[1]) / 2;
            int middle2 = (dataArea[2] + dataArea[3]) / 2;
            for (int j = middle1 - 40; j < middle1 + 40; j++)
            {
                sum = contour[leftFirstLine + 20, lowerBorder, j, j + 40].Sum();
                if ((int)sum > (int)max)
                {
                    max = sum;
                    leftPoint = j + 20;
                }
            }
            max = 0;
            for (int j = middle2 - 40; j < middle2 + 40; j++)
            {
                sum = contour[rightFirstLine + 20, lowerBorder, j, j + 40].Sum();
                if ((int)sum > (int)max)
                {
                    max = sum;
                    rightPoint = j + 20;
                }
            }
            //测距
            leftOrdinate = new int[3];
            rightOrdinate = new int[3];
            int range = 5;
            for (int i = leftFirstLine + 40; i < lowerBorder; i++)
            {
                sum = edge[i, i + 3, leftPoint - range - 5, leftPoint + range + 5].Sum();
                if ((int)sum > 5)
                {
                    leftOrdinate[1] = i;
                    break;
                }
            }
            for (int i = leftOrdinate[0] + 20; i < lowerBorder; i++)
            {
                sum = edge[i, i + 3, leftPoint - range, leftPoint + range].Sum();
                if ((int)sum > 5)
                {
                    leftOrdinate[2] = i;
                    break;
                }
            }
            for (int i = rightFirstLine + 40; i < lowerBorder; i++)
            {
                sum = edge[i, i + 3, rightPoint - range - 5, rightPoint + range + 5].Sum();
                if ((int)sum > 5)
                {
                    rightOrdinate[1] = i;
                    break;
                }
            }
            for (int i = rightOrdinate[0] + 20; i < lowerBorder; i++)
            {
                sum = edge[i, i + 3, rightPoint - range, rightPoint + range].Sum();
                if ((int)sum > 5)
                {
                    rightOrdinate[2] = i;
                    break;
                }
            }
            leftOrdinate[0] = leftPoint;
            rightOrdinate[0] = rightPoint;
        }
        public void GetXigaoZOrdinate2(Mat gray, out int[] leftUpprOrdinate, out int[] rightUpperOrdinate, out int[] leftLwerOrdinate, out int[] rightLowerOrdinate, int upperBorder, int lowerBorder, int[] dataArea)
        {
            if (upperBorder < 0) upperBorder = 0;
            leftUpprOrdinate = new int[3];
            rightUpperOrdinate = new int[3];
            leftLwerOrdinate = new int[3];
            rightLowerOrdinate = new int[3];
            Mat zengqiang = new Mat();
            PointEnhancement(gray, out zengqiang);
            Mat thresh = new Mat();
            double t = Cv2.Threshold(zengqiang, thresh, 0, 255, ThresholdTypes.Otsu);
            thresh = zengqiang.Threshold(t + 65, 1, ThresholdTypes.Binary);
            Scalar sum = new Scalar(0);
            int[] b = new int[2];
            //尋找質量好的位置
            for (int j = 300; j < thresh.Cols - 200; j++)
            {
                sum = thresh[upperBorder, lowerBorder, j, j + 150].Sum();
                if ((int)sum > 4000)
                {
                    b[0] = j;
                    break;
                }
            }
            if (b[0] == 0)
            {
                for (int j = 300; j < thresh.Cols - 200; j++)
                {
                    sum = thresh[upperBorder, lowerBorder, j, j + 150].Sum();
                    if ((int)sum > 3000)
                    {
                        b[0] = j;
                        break;
                    }
                }
            }
            for (int j = b[0] + 300; j < thresh.Cols - 200; j++)
            {
                sum = thresh[upperBorder, lowerBorder, j, j + 150].Sum();
                if ((int)sum > 4000)
                {
                    b[1] = j;
                    break;
                }
            }
            if (b[1] == 0)
            {
                for (int j = b[0] + 300; j < thresh.Cols - 200; j++)
                {
                    sum = thresh[upperBorder, lowerBorder, j, j + 150].Sum();
                    if ((int)sum > 3000)
                    {
                        b[1] = j;
                        break;
                    }
                }
            }
            //精確目標邊界
            int[] border = new int[4];
            for (int j = b[0]; j < thresh.Cols; j += 5)
            {
                sum = thresh[upperBorder, lowerBorder, j, j + 1].Sum();
                if ((int)sum > 0)
                {
                    border[0] = j;
                    break;
                }
            }
            for (int j = border[0] + 50; j < thresh.Cols; j += 5)
            {
                sum = thresh[upperBorder, lowerBorder, j, (j + 10)>= thresh.Width ? thresh.Width-1: (j + 10)].Sum();
                if ((int)sum == 0)
                {
                    border[1] = j;
                    break;
                }
            }
            for (int j = b[1]; j < thresh.Cols; j += 5)
            {
                sum = thresh[upperBorder, lowerBorder, j, j + 1].Sum();
                if ((int)sum > 0)
                {
                    border[2] = j;
                    break;
                }
            }
            for (int j = border[2] + 50; j < thresh.Cols; j += 5)
            {
                sum = thresh[upperBorder, lowerBorder, j, (j + 10) >= thresh.Width ? thresh.Width - 1 : (j + 10)].Sum();
                if ((int)sum == 0)
                {
                    border[3] = j;
                    break;
                }
            }
            //LineShow(gray, b[0], upperBorder, b[0], lowerBorder);
            //LineShow(gray, b[1], upperBorder, b[1], lowerBorder);
            //LineShow(gray, border[0], upperBorder, border[0], lowerBorder);
            //LineShow(gray, border[1], upperBorder, border[1], lowerBorder);
            //LineShow(gray, border[2], upperBorder, border[2], lowerBorder);
            //LineShow(gray, border[3], upperBorder, border[3], lowerBorder);
            //ImageShow(gray, thresh * 255);

            //Mat seClose = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            //Mat close = new Mat();
            //Cv2.MorphologyEx(thresh, close, MorphTypes.Close, seClose);
            Mat sobel = new Mat();
            Sobel(thresh, out sobel);
            Mat result = sobel.Clone();
            //ImageShow(sobel * 255);
            int leftMiddle = (border[0] + border[1]) / 2;
            int rightMiddle = (border[2] + border[3]) / 2;
            int compensate = 5;
            //計算下層測量綫長度
            for (int i = upperBorder + 50; i < upperBorder + 70; i++)
            {
                sum = result[i, i + 1, leftMiddle - 40<0?0: leftMiddle - 40, leftMiddle + 40].Sum();
                if ((int)sum > 50)
                {
                    leftLwerOrdinate[1] = i + compensate;
                    break;
                }
            }
            if (leftLwerOrdinate[1] == 0)
            {
                for (int i = upperBorder + 50; i < upperBorder + 70; i++)
                {
                    sum = result[i, i + 2, leftMiddle - 40 < 0 ? 0 : leftMiddle - 40, leftMiddle + 40].Sum();
                    if ((int)sum > 20)
                    {
                        leftLwerOrdinate[1] = i + compensate;
                        break;
                    }
                }
            }
            for (int i = leftLwerOrdinate[1] + 15; i < lowerBorder + 20; i++)
            {
                sum = result[i, i + 1, leftMiddle - 40 < 0 ? 0 : leftMiddle - 40, leftMiddle + 40].Sum();
                if ((int)sum > 50)
                {
                    leftLwerOrdinate[2] = i + compensate;
                    break;
                }
            }
            if (leftLwerOrdinate[2] == 0)
            {
                for (int i = leftLwerOrdinate[1] + 20; i < lowerBorder + 20; i++)
                {
                    sum = result[i, i + 1, leftMiddle - 40 < 0 ? 0 : leftMiddle - 40, leftMiddle + 40].Sum();
                    if ((int)sum > 20)
                    {
                        leftLwerOrdinate[2] = i + compensate;
                        break;
                    }
                }
            }
            leftLwerOrdinate[0] = (border[0] + border[1]) / 2;

            for (int i = upperBorder + 50; i < upperBorder + 70; i++)
            {
                sum = result[i, i + 1, leftMiddle - 40 < 0 ? 0 : leftMiddle - 40, rightMiddle + 40].Sum();
                if ((int)sum > 50)
                {
                    rightLowerOrdinate[1] = i + compensate;
                    break;
                }
            }
            if (rightLowerOrdinate[1] == 0)
            {
                for (int i = upperBorder + 50; i < upperBorder + 70; i++)
                {
                    sum = result[i, i + 2, leftMiddle - 40 < 0 ? 0 : leftMiddle - 40, rightMiddle + 40].Sum();
                    if ((int)sum > 20)
                    {
                        rightLowerOrdinate[1] = i + compensate;
                        break;
                    }
                }
            }
            for (int i = rightLowerOrdinate[1] + 15; i < lowerBorder + 20; i++)
            {
                sum = result[i, i + 1, leftMiddle - 40 < 0 ? 0 : leftMiddle - 40, rightMiddle + 40].Sum();
                if ((int)sum > 50)
                {
                    rightLowerOrdinate[2] = i + compensate;
                    break;
                }
            }
            rightLowerOrdinate[0] = (border[2] + border[3]) / 2;
            //LineShow(gray, leftLwerOrdinate[0], leftLwerOrdinate[1], leftLwerOrdinate[0], leftLwerOrdinate[2]);
            //LineShow(gray, rightLowerOrdinate[0], rightLowerOrdinate[1], rightLowerOrdinate[0], rightLowerOrdinate[2]);
            //ImageShow(gray, sobel * 255);
            //計算上層測量綫距離
            Mat thresh2 = zengqiang.Threshold(t - 20, 1, ThresholdTypes.Binary);
            Mat sobel2 = new Mat();
            Sobel(thresh2, out sobel2);

            Mat thresh3 = zengqiang.Threshold(t - 10, 1, ThresholdTypes.Binary);
            Mat sobel3 = new Mat();
            Sobel(thresh3, out sobel3);
            for (int i = upperBorder; i < lowerBorder; i++)
            {
                sum = sobel2[i, i + 1, leftMiddle - 60<0?0: leftMiddle - 60, leftMiddle + 60].Sum();
                //if ((int)sum > 5)
                //{
                //    leftUpprOrdinate[1] = 0;
                //    break;
                //}
                //else 
                if ((int)sum > 0)
                {
                    leftUpprOrdinate[1] = i;
                    break;
                }
            }
            for (int i = leftUpprOrdinate[1] + 30; i > leftUpprOrdinate[1] + 7; i--)
            {
                sum = sobel3[i - 1, i, leftMiddle - 60 < 0 ? 0 : leftMiddle - 60, leftMiddle + 60].Sum();
                if ((int)sum > 50)
                {
                    leftUpprOrdinate[2] = i;
                    break;
                }
            }

            leftUpprOrdinate[0] = (border[0] + border[1]) / 2;

            for (int i = upperBorder; i < lowerBorder; i++)
            {
                sum = sobel2[i, i + 1, rightMiddle - 60<0?0 : rightMiddle - 60, rightMiddle + 60].Sum();
                //if ((int)sum > 5)
                //{
                //    rightUpperOrdinate[1] = 0;
                //    break;
                //}
                //else 
                if ((int)sum > 0)
                {
                    rightUpperOrdinate[1] = i;
                    break;
                }
            }
            for (int i = rightUpperOrdinate[1] + 30; i > rightUpperOrdinate[1] + 7; i--)
            {
                sum = sobel3[i - 1, i, rightMiddle - 60 < 0 ? 0 : rightMiddle - 60, rightMiddle + 60].Sum();
                if ((int)sum > 50)
                {
                    rightUpperOrdinate[2] = i;
                    break;
                }
            }
            rightUpperOrdinate[0] = (border[2] + border[3]) / 2;
            //LineShow(gray, leftUpprOrdinate[0], leftUpprOrdinate[1], leftUpprOrdinate[0], leftUpprOrdinate[2]);
            //LineShow(gray, rightUpperOrdinate[0], rightUpperOrdinate[1], rightUpperOrdinate[0], rightUpperOrdinate[2]);
            //ImageShow(gray, (sobel2+sobel3) * 100,sobel3*255);
            if (leftUpprOrdinate[1] == 0 || leftUpprOrdinate[2] == 0)
            {
                leftUpprOrdinate[0] = 0;
                leftUpprOrdinate[1] = 0;
                leftUpprOrdinate[2] = 0;
            }
            if (rightUpperOrdinate[1] == 0 || rightUpperOrdinate[2] == 0)
            {
                rightUpperOrdinate[0] = 0;
                rightUpperOrdinate[1] = 0;
                rightUpperOrdinate[2] = 0;
            }
            if (leftUpprOrdinate[1] != 0 || rightUpperOrdinate[1] != 0)
            {
                for (int i = upperBorder - 10; i < lowerBorder; i++)
                {
                    sum = sobel2[i, i + 1, leftMiddle - 60, leftMiddle + 60].Sum();
                    //if ((int)sum > 5)
                    //{
                    //    leftUpprOrdinate[1] = 0;
                    //    break;
                    //}
                    //else 
                    if ((int)sum > 0)
                    {
                        leftUpprOrdinate[1] = i;
                        break;
                    }
                }
                for (int i = leftUpprOrdinate[1] + 30; i > leftUpprOrdinate[1] + 7; i--)
                {
                    sum = sobel3[i - 1, i, leftMiddle - 60, leftMiddle + 60].Sum();
                    if ((int)sum > 50)
                    {
                        leftUpprOrdinate[2] = i;
                        break;
                    }
                }

                leftUpprOrdinate[0] = (border[0] + border[1]) / 2;

                for (int i = upperBorder - 10; i < lowerBorder; i++)
                {
                    sum = sobel2[i, i + 1, rightMiddle - 60, rightMiddle + 60].Sum();
                    //if ((int)sum > 5)
                    //{
                    //    rightUpperOrdinate[1] = 0;
                    //    break;
                    //}
                    //else 
                    if ((int)sum > 0)
                    {
                        rightUpperOrdinate[1] = i;
                        break;
                    }
                }
                for (int i = rightUpperOrdinate[1] + 30; i > rightUpperOrdinate[1] + 7; i--)
                {
                    sum = sobel3[i - 1, i, rightMiddle - 60, rightMiddle + 60].Sum();
                    if ((int)sum > 50)
                    {
                        rightUpperOrdinate[2] = i;
                        break;
                    }
                }
            }
            //CvTrackbarCallback cvTrackbarCallback = new CvTrackbarCallback(Text);
            //Window window = new Window("tbar");//创建一个新窗口"tbar"
            //CvTrackbar cvTrackbarV = new CvTrackbar("bar1", "tbar", 0, 255, cvTrackbarCallback);

            //Cv2.WaitKey();
            //void Text(int value)
            //{
            //    thresh = zengqiang.Threshold(t - value, 255, ThresholdTypes.Binary);
            //    new Window("tbar", thresh);
            //}

        }
        //公用
        /// <summary>
        /// 去除圓形
        /// </summary>
        /// <param name="image1"></param>
        /// <param name="image2"></param>
        /// <param name="result"></param>
        /// <param name="dp">累加器分辨率与图像分辨率的反比。默认=1</param>
        /// <param name="minDist">检测到的圆的中心之间的最小距离。</param>
        /// <param name="param1">第一个方法特定的参数</param>
        /// <param name="param2">第二个方法特定于参数</param>
        /// <param name="minRadius">最小半径</param>
        /// <param name="maxRadius">最大半径</param>
        public void RemoveCircles(Mat image1, Mat image2, out Mat result, double dp, double minDist, double param1, double param2, int minRadius, int maxRadius)
        {
            result = 1 - image2.Clone();
            int range = 10;
            //ImageShow(result*255);
            //dp = 1;
            //minDist = 30;
            //param1 = 70;
            //param2 = 30;
            //minRadius = 10;
            //maxRadius = 60;
            CircleSegment[] circles = Cv2.HoughCircles(image1, HoughMethods.Gradient, dp, minDist, param1, param2, minRadius, maxRadius);
            for (int i = 0; i < circles.Length; i++)
            {
                Point center = (Point)circles[i].Center;
                int radius = (int)circles[i].Radius;
                //for(int j=1;j<radius;j++)
                //Cv2.Circle(result, center, j, new Scalar(1));    
                Cv2.Rectangle(result, new Rect(center.X - radius - range, center.Y - radius - range, 2 * (radius + range), 2 * (radius + range)), new Scalar(1), -1);
            }
            result = 1 - result;
            //ImageShow(result*255);
        }
        public void RemoveCircles(Mat image1, Mat image2, out Mat result)
        {
            RemoveCircles(image1, image2, out result, 1, 30, 70, 30, 10, 60);
        }
        public void RemoveCircles(Mat image, out Mat result)
        {
            result = new Mat(image.Size(), image.Type());
            Mat hierachy = new Mat();
            Mat[] contoursMat;
            Cv2.FindContours(image, out contoursMat, hierachy, RetrievalModes.External, ContourApproximationModes.ApproxNone);

            Point[][] contours;
            HierarchyIndex[] hierarchyIndices;
            Cv2.FindContours(image, out contours, out hierarchyIndices, RetrievalModes.External, ContourApproximationModes.ApproxNone);
            for (int i = 0; i < contours.Count(); i++)
            {
                if (contours[i].Count() < 10)
                    continue;
                else
                {
                    int[] x = new int[contours[i].Count()];
                    int[] y = new int[contours[i].Count()];
                    for (int j = 0; j < contours[i].Count(); j++)
                    {
                        x[j] = contours[i][j].X;
                        y[j] = contours[i][j].Y;
                    }
                    double maxY = y.Max();
                    double minY = y.Min();
                    double maxX = x.Max();
                    double minX = x.Min();
                    double hengzongbi = (double)((maxX - minX) / (maxY - minY));
                    if (hengzongbi > 1.8 || hengzongbi < 0.5)
                    {
                        Cv2.DrawContours(result, contoursMat, i, new Scalar(1));
                    }
                }
            }
            Fill(result, out result, 1);
        }
        /// <summary>
        /// 保留近似直线
        /// </summary>
        /// <param name="image"></param>
        /// <param name="result"></param>
        public void KeepStraight(Mat image, out Mat result, out List<int> ordinates)
        {
            result = new Mat(image.Size(), image.Type());
            ordinates = new List<int>();
            Mat hierachy = new Mat();
            Mat[] contoursMat;
            Cv2.FindContours(image, out contoursMat, hierachy, RetrievalModes.External, ContourApproximationModes.ApproxNone);

            Point[][] contours;
            HierarchyIndex[] hierarchyIndices;
            Cv2.FindContours(image, out contours, out hierarchyIndices, RetrievalModes.External, ContourApproximationModes.ApproxNone);
            for (int i = 0; i < contours.Count(); i++)
            {
                if (contours[i].Count() < 10)
                    continue;
                else
                {
                    int[] x = new int[contours[i].Count()];
                    int[] y = new int[contours[i].Count()];
                    for (int j = 0; j < contours[i].Count(); j++)
                    {
                        x[j] = contours[i][j].X;
                        y[j] = contours[i][j].Y;
                    }
                    double maxY = y.Max();
                    double minY = y.Min();
                    double maxX = x.Max();
                    double minX = x.Min();
                    double hengzongbi = (double)((maxX - minX) / (maxY - minY));
                    if (hengzongbi > 20 || hengzongbi < 0.1)
                    {
                        Cv2.DrawContours(result, contoursMat, i, new Scalar(1));
                        //int newOrdinate = (int)(maxY+minY)/2;
                        int newOrdinate = (int)minY + 5;
                        ordinates.Add(newOrdinate);
                    }
                }
            }
            //Fill(result, out result, 1);
        }


        /// <summary>
        /// 保留最大连通域为1，其余为0
        /// </summary>
        /// <param name="image"></param>
        /// <param name="result"></param>
        public void GetMaxArea(Mat image, out Mat result)
        {
            Mat[] contours;
            Mat hierachy = new Mat();
            Cv2.FindContours(image, out contours, hierachy, RetrievalModes.External, ContourApproximationModes.ApproxNone);

            double max_area = 0;
            int index = 0;
            for (int i = 0; i < contours.Count(); i++)
            {
                if (Cv2.ContourArea(contours[i]) > max_area)
                {
                    max_area = Cv2.ContourArea(contours[i]);
                    index = i;
                }
            }

            result = Mat.Zeros(image.Rows, image.Cols, image.Type());
            Cv2.DrawContours(result, contours, index, new Scalar(1));
            Fill(result, out result, 1);
            //ImageShow(image*255,result * 255);

        }
        /// <summary>
        /// 保留面积大于或小于某个值的连通域
        /// </summary>
        /// <param name="contour"></param>
        /// <param name="result"></param>
        /// <param name="value"></param>
        /// <param name="compare">true：大于；false：小于</param>
        public void GetArea(Mat contour, out Mat result, int value, bool compare)
        {
            result = Mat.Zeros(contour.Rows, contour.Cols, contour.Type());
            Mat[] contours;
            Mat hierachy = new Mat();
            Cv2.FindContours(contour, out contours, hierachy, RetrievalModes.External, ContourApproximationModes.ApproxNone);

            for (int i = 0; i < contours.Count(); i++)
            {
                switch (compare)
                {
                    case true:
                        if (Cv2.ContourArea(contours[i]) > value)
                        {
                            Cv2.DrawContours(result, contours, i, new Scalar(1));
                        }
                        break;
                    case false:
                        if (Cv2.ContourArea(contours[i]) < value)
                        {
                            Cv2.DrawContours(result, contours, i, new Scalar(1));
                        }
                        break;
                }

            }
            Fill(result, out result, 1);
        }
        public void GetAreaNoFill(Mat contour, out Mat result, int value, bool compare)
        {
            result = Mat.Zeros(contour.Rows, contour.Cols, contour.Type());
            Mat[] contours;
            Mat hierachy = new Mat();
            Cv2.FindContours(contour, out contours, hierachy, RetrievalModes.External, ContourApproximationModes.ApproxNone);

            for (int i = 0; i < contours.Count(); i++)
            {
                switch (compare)
                {
                    case true:
                        if (Cv2.ContourArea(contours[i]) > value)
                        {
                            Cv2.DrawContours(result, contours, i, new Scalar(1));
                        }
                        break;
                    case false:
                        if (Cv2.ContourArea(contours[i]) < value)
                        {
                            Cv2.DrawContours(result, contours, i, new Scalar(1));
                        }
                        break;
                }

            }
            //Fill(result, out result, 1);
        }

        /// <summary>
        /// 得到最大连通域的轮廓图
        /// </summary>
        /// <param name="image"></param>
        /// <param name="result"></param>
        public void GetMaxContour(Mat image, out Mat result)
        {
            Mat[] contours;
            Mat hierachy = new Mat();
            Cv2.FindContours(image, out contours, hierachy, RetrievalModes.External, ContourApproximationModes.ApproxNone);

            double max_area = 0;
            int index = 0;
            for (int i = 0; i < contours.Count(); i++)
            {
                if (Cv2.ContourArea(contours[i]) > max_area)
                {
                    max_area = Cv2.ContourArea(contours[i]);
                    index = i;
                }
            }

            result = Mat.Zeros(image.Rows, image.Cols, image.Type());
            Cv2.DrawContours(result, contours, index, new Scalar(1));
        }
        /// <summary>
        /// 得到图像中非零点的坐标
        /// </summary>
        /// <param name="image"></param>
        /// <param name="ordinates"></param>
        public void FindContourOrdinate(Mat image, out Point[] ordinates)
        {
            int nonZeroNumber = Cv2.CountNonZero(image);
            ordinates = new Point[nonZeroNumber];
            int count = 0;
            for (int i = 0; i < image.Rows; i++)
            {
                for (int j = 0; j < image.Cols; j++)
                {
                    if (image.Get<byte>(i, j) > 0)
                    {
                        ordinates[count].X = j;
                        ordinates[count].Y = i;
                    }
                }
            }

        }
        /// <summary>
        /// 填充图片孔洞
        /// </summary>
        /// <param name="image">输入二值图像</param>
        /// <param name="result">输出图像</param>
        /// <param name="value">填充像素值</param>
        public void Fill(Mat image, out Mat result, int value)
        {
            Size imageSize = image.Size();
            Mat kuozhan = Mat.Zeros(imageSize.Height + 2, imageSize.Width + 2, image.Type());
            image.CopyTo(kuozhan[1, imageSize.Height + 1, 1, imageSize.Width + 1]);
            Cv2.FloodFill(kuozhan, new Point(0, 0), new Scalar(value));
            Mat crop = kuozhan[1, imageSize.Height + 1, 1, imageSize.Width + 1];
            result = image + value - crop;
        }
        /// <summary>
        /// 对图片进行sobel边缘检测
        /// </summary>
        /// <param name="imageContour"></param>
        /// <param name="imageSobel"></param>
        public void Sobel(Mat imageContour, out Mat imageSobel)
        {
            //横向检测
            Mat grad_x = new Mat();
            Mat grad_x2 = new Mat();
            Cv2.Sobel(imageContour, grad_x, MatType.CV_16S, 1, 0);
            Cv2.ConvertScaleAbs(grad_x, grad_x2);
            //纵向检测
            Mat grad_y = new Mat();
            Mat grad_y2 = new Mat();
            Cv2.Sobel(imageContour, grad_y, MatType.CV_16S, 0, 1);
            Cv2.ConvertScaleAbs(grad_y, grad_y2);
            //横纵向混合平均
            imageSobel = new Mat();
            Cv2.AddWeighted(grad_x2, 0.5, grad_y2, 0.5, 0, imageSobel);
        }
        /// <summary>
        /// 比较两个数的大小
        /// </summary>
        /// <param name="a"></param>
        /// <param name="b"></param>
        /// <param name="world">输入选项，big，small</param>
        /// <param name="result">输出大值或小值</param>
        public void ChooseSize(double a, double b, string world, out double result)
        {
            result = 0;
            switch (world)
            {
                case "big":
                    if (a > b)
                    {
                        result = a;
                    }
                    else
                    {
                        result = b;
                    }
                    break;
                case "small":
                    if (a < b)
                    {
                        result = a;
                    }
                    else
                    {
                        result = b;
                    }
                    break;
            }
        }
        /// <summary>
        /// 判断是否有水平直线
        /// </summary>
        /// <param name="image"></param>
        /// <param name="ordinate">输出直线纵坐标</param>
        /// <param name="border">判断区域</param>
        public void DetectStraightLine(Mat image, out int ordinate, int[] border)
        {
            /*
             * 得到每个连通域的坐标集
             * 求每个连通域坐标集最大最小横纵坐标
             * 求横纵长度
             * 同时满足左右长度和上下长度的阈值条件，判定为直线
             */
            ordinate = 0;
            Mat crop = image[border[0], border[1], 0, image.Cols].Clone();

            //Mat hierachy = new Mat();
            //Mat[] contours;
            //Cv2.FindContours(crop, out contours, hierachy, RetrievalModes.External, ContourApproximationModes.ApproxNone);

            Point[][] contours;
            HierarchyIndex[] hierarchyIndices;
            Cv2.FindContours(crop, out contours, out hierarchyIndices, RetrievalModes.External, ContourApproximationModes.ApproxNone);
            Mat idx = new Mat();

            for (int i = 0; i < contours.Count(); i++)
            {
                if (contours[i].Count() < 200 || contours[i].Count() > 4000)
                    continue;
                else
                {
                    int[] x = new int[contours[i].Count()];
                    int[] y = new int[contours[i].Count()];
                    for (int j = 0; j < contours[i].Count(); j++)
                    {
                        x[j] = contours[i][j].X;
                        y[j] = contours[i][j].Y;
                    }
                    int maxY = y.Max();
                    int minY = y.Min();
                    int maxX = x.Max();
                    int minX = x.Min();
                    if ((maxY - minY) < 25 && (maxX - minX) > 250)
                    {
                        ordinate = (maxY + minY) / 2 + border[0];
                        break;
                    }

                }
            }
        }
        public void LineShow(Mat image, int x1, int y1, int x2, int y2)
        {
            Point p1 = new Point();
            Point p2 = new Point();
            p1.X = x1;
            p1.Y = y1;
            p2.X = x2;
            p2.Y = y2;
            Scalar color = new Scalar(0, 0, 255);
            //颜色
            Cv2.Line(image, p1, p2, color, 2, LineTypes.Link8);
        }
        /// <summary>
        /// 图像画线，线颜色是红色
        /// </summary>
        /// <param name="image"></param>
        /// <param name="point1"></param>
        /// <param name="point2"></param>
        public void LineShow(Mat image, Point point1, Point point2)
        {
            Scalar color = new Scalar(0, 0, 255);
            //颜色
            Cv2.Line(image, point1, point2, color, 2, LineTypes.Link8);
        }
        /// <summary>
        /// 图像画线，线条颜色可以选择红，绿，蓝
        /// </summary>
        /// <param name="image">画线图像</param>
        /// <param name="x1"></param>
        /// <param name="y1"></param>
        /// <param name="x2"></param>
        /// <param name="y2"></param>
        /// <param name="colorChoose">颜色选择，red、blue、green</param>
        public void LineShow(Mat image, int x1, int y1, int x2, int y2, string colorChoose)
        {
            Point p1 = new Point();
            Point p2 = new Point();
            p1.X = x1;
            p1.Y = y1;
            p2.X = x2;
            p2.Y = y2;
            Scalar color = new Scalar();//颜色
            switch (colorChoose)
            {
                case "blue":
                    color = new Scalar(255, 0, 0);
                    break;
                case "green":
                    color = new Scalar(0, 255, 0);
                    break;
                case "red":
                    color = new Scalar(0, 0, 255);
                    break;
                default:
                    break;
            }
            Cv2.Line(image, p1, p2, color, 2, LineTypes.Link8);
        }
        /// <summary>
        /// 图像画线，线条颜色可以选择红，绿，蓝
        /// </summary>
        /// <param name="image"></param>
        /// <param name="point1"></param>
        /// <param name="point2"></param>
        /// <param name="colorChoose">颜色选择，red、blue、green</param>
        public void LineShow(Mat image, Point point1, Point point2, string colorChoose)
        {
            Scalar color = new Scalar();//颜色
            switch (colorChoose)
            {
                case "blue":
                    color = new Scalar(255, 0, 0);
                    break;
                case "green":
                    color = new Scalar(0, 255, 0);
                    break;
                case "red":
                    color = new Scalar(0, 0, 255);
                    break;
                default:
                    break;
            }
            Cv2.Line(image, point1, point2, color, 2, LineTypes.Link8);
        }
        /// <summary>
        /// 图片显示数字，两位小数
        /// </summary>
        /// <param name="image"></param>
        /// <param name="data"></param>
        /// <param name="x"></param>
        /// <param name="y"></param>
        public void TextShow(Mat image, double data, int x, int y)
        {
            data = Math.Round(data, 2);
            Scalar color = new Scalar(255, 0, 0);
            Point p = new Point();
            p.X = x;
            p.Y = y;
            Cv2.PutText(image, data.ToString() + "um", p, HersheyFonts.HersheyComplex, 0.8, color, 2, LineTypes.Link8);
        }
        /// <summary>
        /// 图像线条标记（竖向）
        /// </summary>
        /// <param name="image"></param>
        /// <param name="point1"></param>
        /// <param name="point2"></param>
        /// <param name="data"></param>
        public void LabelVertical(Mat image, Point point1, Point point2, double data)
        {
            double proportion = 0.2689;
            data = data * proportion;
            double middle = (point1.Y + point2.Y) / 2;
            LineShow(image, point1, point2, "blue");
            LineShow(image, point1.X - 5, point1.Y, point1.X + 5, point1.Y, "blue");
            LineShow(image, point2.X - 5, point2.Y, point2.X + 5, point2.Y, "blue");

            TextShow(image, data, point1.X, (int)middle);
        }
        /// <summary>
        /// 图像线条标记（橫向）
        /// </summary>
        /// <param name="image"></param>
        /// <param name="point1"></param>
        /// <param name="point2"></param>
        /// <param name="data"></param>
        public void LabelHorizontal(Mat image, Point point1, Point point2, double data)
        {
            double proportion = 0.2689;
            data = data * proportion;
            double middle = (point1.X + point2.X) / 2;
            LineShow(image, point1, point2, "blue");
            LineShow(image, point1.X, point1.Y - 5, point1.X, point1.Y + 5, "blue");
            LineShow(image, point2.X, point2.Y - 5, point2.X, point2.Y + 5, "blue");
            TextShow(image, data, (int)middle, point1.Y);
        }
        public void ImageShow(Mat image1)
        {
            new Window("image1", WindowMode.Normal, image1);
            Cv2.WaitKey();
        }
        public void ImageShow(Mat image1, Mat image2)
        {
            new Window("image1", WindowMode.Normal, image1);
            new Window("image2", WindowMode.Normal, image2);
            Cv2.WaitKey();
        }
        public void ImageShow(Mat image1, Mat image2, Mat image3)
        {
            new Window("image1", WindowMode.Normal, image1);
            new Window("image2", WindowMode.Normal, image2);
            new Window("image3", WindowMode.Normal, image3);
            Cv2.WaitKey();
        }
        public void ImageShow(Mat image1, Mat image2, Mat image3, Mat image4)
        {
            new Window("image1", WindowMode.Normal, image1);
            new Window("image2", WindowMode.Normal, image2);
            new Window("image3", WindowMode.Normal, image3);
            new Window("image4", WindowMode.Normal, image4);
            Cv2.WaitKey();
        }
        public void ImageShow(Mat image1, Mat image2, Mat image3, Mat image4, Mat image5)
        {
            new Window("image1", WindowMode.Normal, image1);
            new Window("image2", WindowMode.Normal, image2);
            new Window("image3", WindowMode.Normal, image3);
            new Window("image4", WindowMode.Normal, image4);
            new Window("image5", WindowMode.Normal, image5);
            Cv2.WaitKey();
        }
        /// <summary>
        /// 点增强
        /// </summary>
        /// <param name="image"></param>
        /// <param name="result"></param>
        public void PointEnhancement(Mat image, out Mat result)
        {
            result = new Mat(image.Size(), image.Type());
            InputArray kernel = InputArray.Create<int>(new int[3, 3] { { 0, -1, 0 }, { -1, 5, -1 }, { 0, -1, 0 } });
            Cv2.Filter2D(image, result, -1, kernel);
            Cv2.ConvertScaleAbs(result, result);
        }
        public void LineEnhancement(Mat image, out Mat result)
        {
            result = new Mat(image.Size(), image.Type());
            InputArray kernel = InputArray.Create<int>(new int[3, 3] { { -1, -1, -1 }, { 1, 5, 1 }, { -1, -1, -1 } });
            Cv2.Filter2D(image, result, -1, kernel);
            //result += 100;
            Cv2.ConvertScaleAbs(result, result);
        }
        /// <summary>
        /// 纵向边缘检测
        /// </summary>
        /// <param name="image"></param>
        /// <param name="result"></param>
        public void EdgeY(Mat image, out Mat result)
        {
            InputArray kernel1 = InputArray.Create<int>(new int[3, 3] { { -5, -10, -5 }, { 0, 0, 0 }, { 5, 10, 5 } });
            InputArray kernel2 = InputArray.Create<int>(new int[3, 3] { { 5, 10, 5 }, { 0, 0, 0 }, { -5, -10, -5 } });
            Mat result1 = new Mat();
            Mat result2 = new Mat();
            Cv2.Filter2D(image, result1, MatType.CV_16SC1, kernel1);
            Cv2.Filter2D(image, result2, MatType.CV_16SC1, kernel2);
            Cv2.ConvertScaleAbs(result1, result1);
            Cv2.ConvertScaleAbs(result2, result2);
            result = new Mat();
            Cv2.AddWeighted(result1, 0.5, result2, 0.5, 0, result);
        }
        public void EdgeY2(Mat image, out Mat result)
        {
            InputArray kernel1 = InputArray.Create<int>(new int[3, 9] { { -5, -5, -5, -5, -5, -5, -5, -5, -5 }, { 0, 0, 0, 0, 0, 0, 0, 0, 0 }, { 5, 5, 5, 5, 5, 5, 5, 5, 5 } });
            InputArray kernel2 = InputArray.Create<int>(new int[3, 9] { { 5, 5, 5, 5, 5, 5, 5, 5, 5 }, { 0, 0, 0, 0, 0, 0, 0, 0, 0 }, { -5, -5, -5, -5, -5, -5, -5, -5, -5 } });
            Mat result1 = new Mat();
            Mat result2 = new Mat();
            Cv2.Filter2D(image, result1, MatType.CV_16SC1, kernel1);
            Cv2.Filter2D(image, result2, MatType.CV_16SC1, kernel2);
            Cv2.ConvertScaleAbs(result1, result1);
            Cv2.ConvertScaleAbs(result2, result2);
            result = new Mat();
            Cv2.AddWeighted(result1, 0.5, result2, 0.5, 0, result);
        }
        /// <summary>
        /// 横向边缘检测
        /// </summary>
        /// <param name="image"></param>
        /// <param name="result"></param>
        public void EdgeX(Mat image, out Mat result)
        {
            InputArray kernel1 = InputArray.Create<int>(new int[3, 3] { { -5, 0, 5 }, { -10, 0, 10 }, { -5, 0, 5 } });
            InputArray kernel2 = InputArray.Create<int>(new int[3, 3] { { 5, 0, -5 }, { 10, 0, -10 }, { 5, 0, -5 } });
            Mat result1 = new Mat();
            Mat result2 = new Mat();
            Cv2.Filter2D(image, result1, MatType.CV_16SC1, kernel1);
            Cv2.Filter2D(image, result2, MatType.CV_16SC1, kernel2);
            Cv2.ConvertScaleAbs(result1, result1);
            Cv2.ConvertScaleAbs(result2, result2);
            result = new Mat();
            Cv2.AddWeighted(result1, 0.5, result2, 0.5, 0, result);
        }

        /// <summary>
        /// 边缘检测，横向边缘检测与纵向边缘检测的均值
        /// </summary>
        /// <param name="image"></param>
        /// <param name="result"></param>
        public void Edge(Mat image, out Mat result)
        {
            result = new Mat();
            Mat result1 = new Mat();
            Mat result2 = new Mat();
            EdgeX(image, out result1);
            EdgeY(image, out result2);
            Cv2.AddWeighted(result1, 0.5, result2, 0.5, 0, result);
        }
        /// <summary>
        /// 求一组坐标点的平均坐标值，去掉最大横纵坐标和最小横纵坐标
        /// </summary>
        /// <param name="x"></param>
        /// <param name="y"></param>
        /// <param name="averOrdinate"></param>
        public void AverOrdinate(int[] x, int[] y, out double[] averOrdinate)
        {
            averOrdinate = new double[2];
            int length = x.Length;
            int maxX = 0, minX = 0, maxY = 0, minY = 0;
            maxX = x.Max();
            minX = x.Min();
            maxY = y.Max();
            minY = y.Min();
            int[] newX = new int[length - 2];
            int[] newY = new int[length - 2];
            bool maxTag = false;
            bool minTag = false;
            int count = 0;
            int zeroX = 0;
            int zeroY = 0;
            for (int i = 0; i < length; i++)
            {
                if (x[i] == maxX && maxTag == false)
                {
                    maxTag = true;
                    continue;
                }
                else if (x[i] == minX && minTag == false)
                {
                    minTag = true;
                    continue;
                }
                else if (x[i] != 0)
                {
                    newX[count] = x[i];
                    count++;
                }
                else if (x[i] == 0)
                    zeroX++;

            }
            maxTag = false;
            minTag = false;
            count = 0;
            for (int i = 0; i < length; i++)
            {
                if (y[i] == maxY && maxTag == false)
                {
                    maxTag = true;
                    continue;
                }
                else if (y[i] == minY && minTag == false)
                {
                    minTag = true;
                    continue;
                }
                else if (y[i] != 0)
                {
                    newY[count] = y[i];
                    count++;
                }
                else if (y[i] == 0)
                    zeroY++;
            }
            double averX = ((newX.Length - zeroX) == 0) ? 0 : newX.Sum() / (newX.Length - zeroX);
            double averY = ((newY.Length - zeroY) == 0) ? 0 : newY.Sum() / (newY.Length - zeroY);
            averOrdinate[0] = averX;
            averOrdinate[1] = averY;

        }
        /// <summary>
        /// 得到图中非零点的坐标
        /// </summary>
        /// <param name="image"></param>
        /// <param name="idx"></param>
        public void FindNonZeros(Mat image, out Point[] idx)
        {
            Mat thresh = image.Threshold(0, 1, ThresholdTypes.Binary);
            int num = (int)thresh.Sum();//不为0点的数量
            idx = new Point[num];
            int count = 0;
            for (int i = 0; i < image.Rows; i++)
            {
                if ((int)image[i, i + 1, 0, image.Cols].Sum() != 0)
                {
                    for (int j = 0; j < image.Cols; j++)
                    {
                        if (image.Get<byte>(i, j) > 0)
                        {
                            idx[count].X = j;
                            idx[count].Y = i;
                            count++;
                        }
                    }
                }
            }
        }
        /// <summary>
        /// 得到图中非零点最左上角的坐标
        /// </summary>
        /// <param name="image"></param>
        /// <param name="leftTop"></param>
        public void FindLeftTop(Mat image, out Point leftTop)
        {
            leftTop = new Point();
            Point[] idx;
            FindNonZeros(image, out idx);
            int min = 1000000;
            for (int i = 0; i < idx.Length; i++)
            {
                if (min > (idx[i].X + idx[i].Y))
                {
                    min = idx[i].X + idx[i].Y;
                    leftTop.X = idx[i].X;
                    leftTop.Y = idx[i].Y;
                }
            }
        }
    }

}