SANAS/ceju/Class1.cs

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using OpenCvSharp;
using System.Collections;


namespace ceju
{
    class Classification
    {
        public static void Qianmangkong(string fileName)
        {   //获取图片
            Mat image = new Mat(fileName, ImreadModes.Color);
            //获取图片的长宽
            int rows = image.Rows;
            int cols = image.Cols;
            //将图片转换为灰度图片
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);
            //获取图片的通道数
            int channels = image.Channels();
            //获得蓝色，绿色，红色通道图片
            Mat imageBlue,imageGreen,imageRed = new Mat(imageGray.Size(), imageGray.Type());
            SubFunction.SeparateRGB(image, out imageBlue, out imageGreen, out imageRed);
            double proportion = 0.2689;
            /* 
             *  一、
             *  1、对图像进行阈值分割，选取目标区域，阈值选取用Otsu方法
             *  2、对于一些小的孔洞进行填充(没实现，待定)   
             *  3、进行sobel算子的边缘检测,横纵向边缘的平均
             *  4、去掉小面积（没实现，待定）
             * 
             */
            //Otsu阈值分割
            Mat imageThresh = imageRed.Threshold(0, 255, ThresholdTypes.Otsu);//最大值调成1的话显示不出来，在转换成数组的时候注意255要变成1
            //sobel算子边缘检测
            //横向检测
            Mat grad_x = new Mat();
            Mat grad_x2 = new Mat();
            Cv2.Sobel(imageThresh, 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(imageThresh, grad_y, MatType.CV_16S, 0, 1);
            Cv2.ConvertScaleAbs(grad_y, grad_y2);
            //横纵向混合平均
            Mat imageSobel = new Mat();
            Cv2.AddWeighted(grad_x2, 0.5, grad_y2, 0.5, 0, imageSobel);
            //将imageThresh的Mat类转换成数组,并且是0，1二值
            //将Mat类中的数组转为数组
            int[,] arrayThresh = BasFunction.Mat2Array(imageThresh);
            //将数组转为0，1数组
            arrayThresh = BasFunction.ConversionRange(arrayThresh);
            //将sobel边缘检测后的轮廓线转为0，1二值
            int[,] arraySobel = BasFunction.Mat2Array(imageSobel);
            arraySobel = BasFunction.ConversionRange(arraySobel);

            // 二、计算中部区域的边界，middleArea[0]中部左边界，middleArea[1]中部右边界
            int[] middleArea = SubFunction.GetMiddleArea(imageThresh);
            //显示线条
            //SubFunction.LineShow(image, middleArea[0], 0, middleArea[0], rows,"red");
            //SubFunction.LineShow(image, middleArea[1], 0, middleArea[1], rows,"green");
            //new Window("middleArea", WindowMode.Normal, image);
            //Cv2.WaitKey(0);
            // 三、计算数据提取区域的边界
            //dataArea[0]左部分左边界，dataArea[1]左部分右边界，dataArea[2]右部分左边界，dataArea[3]右部分右边界
            int[] dataArea = SubFunction.GetDataArea(imageThresh,middleArea);
            //叠加线条
            //SubFunction.LineShow(image, dataArea[0], 0, dataArea[0], rows,"red");
            //SubFunction.LineShow(image, dataArea[1], 0, dataArea[1], rows,"green");
            //SubFunction.LineShow(image, dataArea[2], 0, dataArea[2], rows,"blue");
            //SubFunction.LineShow(image, dataArea[3], 0, dataArea[3], rows,"red");
            //new Window("middleArea", WindowMode.Normal, image);
            //Cv2.WaitKey(0);
            // 四、提取L1、L3、L4、L5
            //腐蚀结构[1,1,1];
            Mat seErode = Cv2.GetStructuringElement(MorphShapes.Rect,new Size(3,1));
            //腐蚀
            Mat outLine = new Mat();//轮廓线
            Cv2.Erode(imageSobel, outLine, seErode);
            //将轮廓线的腐蚀后转为0，1二值
            int[,] arrayOutline = BasFunction.Mat2Array(outLine);
            arrayOutline = BasFunction.ConversionRange(arrayOutline);

            //提取线条
            //线条L1数组
            int[,] line1 = new int[rows, cols];
            //L1的纵坐标
            double averageCoordinate1 = 0;
            //得到L1，以及L1的平均纵坐标。
            SubFunction.ExtractLines(arraySobel,out line1,out averageCoordinate1, dataArea[0], dataArea[3]);
            //得到L1左部分，以及平均纵坐标
            int[,] lineLeft1 = new int[rows, cols];
            double meanOrdinateLeft1 = 0;
            SubFunction.ExtractLines(arraySobel, out lineLeft1, out meanOrdinateLeft1, dataArea[0], dataArea[1]);
            //得到L3左部分，以及平均纵坐标
            int[,] lineLeft3 = new int[rows, cols];
            double meanOrdinateLeft3 = 0;
            SubFunction.ExtractLines(arraySobel,out lineLeft3, out meanOrdinateLeft3, dataArea[0], dataArea[1], meanOrdinateLeft1);
            //得到L4左部分，以及平均纵坐标
            int[,] lineLeft4 = new int[rows, cols];
            double meanOrdinateLeft4 = 0;
            SubFunction.ExtractLines(arrayOutline, out lineLeft4, out meanOrdinateLeft4, dataArea[0], dataArea[1], meanOrdinateLeft3);
            //得到L5左部分，以及平均纵坐标
            int[,] lineLeft5 = new int[rows, cols];
            double meanOrdinateLeft5 = 0;
            SubFunction.ExtractLines(arrayOutline, out lineLeft5, out meanOrdinateLeft5, dataArea[0], dataArea[1], meanOrdinateLeft4);
            //得到L1右部分，以及平均纵坐标
            int[,] lineRight1 = new int[rows, cols];
            double meanOrdinateRight1 = 0;
            SubFunction.ExtractLines(arraySobel, out lineRight1, out meanOrdinateRight1, dataArea[2], dataArea[3]);
            //得到L3右部分，以及平均纵坐标
            int[,] lineRight3 = new int[rows, cols];
            double meanOrdinateRight3 = 0;
            SubFunction.ExtractLines(arraySobel, out lineRight3, out meanOrdinateRight3, dataArea[2], dataArea[3], meanOrdinateRight1);
            //得到L4右部分，以及平均纵坐标
            int[,] lineRight4 = new int[rows, cols];
            double meanOrdinateRight4 = 0;
            SubFunction.ExtractLines(arrayOutline, out lineRight4, out meanOrdinateRight4, dataArea[2], dataArea[3], meanOrdinateRight3);
            //得到L5右部分，以及平均纵坐标
            int[,] lineRight5 = new int[rows, cols];
            double meanOrdinateRight5 = 0;           
            SubFunction.ExtractLines(arrayOutline, out lineRight5, out meanOrdinateRight5, dataArea[2], dataArea[3], meanOrdinateRight4);
            //显示线条重叠
            SubFunction.LineShow(image, dataArea[0], (int)meanOrdinateLeft1, dataArea[1], (int)meanOrdinateLeft1);
            SubFunction.LineShow(image, dataArea[0], (int)meanOrdinateLeft3, dataArea[1], (int)meanOrdinateLeft3);
            SubFunction.LineShow(image, dataArea[0], (int)meanOrdinateLeft4, dataArea[1], (int)meanOrdinateLeft4);
            SubFunction.LineShow(image, dataArea[0], (int)meanOrdinateLeft5, dataArea[1], (int)meanOrdinateLeft5);
            SubFunction.LineShow(image, dataArea[2], (int)meanOrdinateRight1, dataArea[3], (int)meanOrdinateRight1);
            SubFunction.LineShow(image, dataArea[2], (int)meanOrdinateRight3, dataArea[3], (int)meanOrdinateRight3);
            SubFunction.LineShow(image, dataArea[2], (int)meanOrdinateRight4, dataArea[3], (int)meanOrdinateRight4);
            SubFunction.LineShow(image, dataArea[2], (int)meanOrdinateRight5, dataArea[3], (int)meanOrdinateRight5);
            //new Window("middleArea", WindowMode.Normal, image);
            //Cv2.WaitKey(0);
 
            //五、求L2           
            double meanOrdinateLeft2 = 0;
            double meanOrdinateRight2 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateLeft1 + 10, (int)meanOrdinateLeft3 - 10, dataArea[0], dataArea[1], out meanOrdinateLeft2);
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateRight1 + 10, (int)meanOrdinateRight3 - 10, dataArea[2], dataArea[3], out meanOrdinateRight2);
            
            //七、孔铜
            //得到孔径起止点
            //aperture[0]孔径起始点（左）；aperture[1]孔径起始点（右）
            int[] aperture = new int[2];
            SubFunction.GetAperture(arrayThresh,out aperture, (int)meanOrdinateLeft3, (int)meanOrdinateRight3, middleArea, dataArea);
            int[] apertureBegin = { (int)meanOrdinateLeft3, aperture[0] };
            int[] apertureEnd = { (int)meanOrdinateRight3, aperture[1] };
            //孔径中点
            double middleAperture = (aperture[0] + aperture[1]) / 2;
            //求孔径起始点与曲面之间的最短距离，以及最短距离时的曲面坐标
            double[] kongtong = new double[2];
            int[] pointLeft = new int[2];
            int[] pointRight = new int[2];
            SubFunction.GetKongtong(line1, apertureBegin, apertureEnd, out kongtong,out pointLeft,out pointRight);
            
            //九、下孔径
            int[] apertureLow = new int[2];
            SubFunction.GetAperture(arrayThresh, out apertureLow, (int)meanOrdinateLeft4, (int)meanOrdinateRight4, middleArea, dataArea);
            //十、孔底与孔深
            //提取曲面最凸点坐标
            int[] curveVertex = new int[2];
            //孔径平均高度
            double middleApertureY;
            SubFunction.CurveVertex(line1, apertureBegin, apertureEnd, out curveVertex,out middleApertureY);

            //六、求L6
            double t1 = 0;
            double t2 = 0;
            double meanOrdinateL6 = 0;
            BasFunction.ChooseSize(meanOrdinateLeft4, meanOrdinateRight4, "small", out t1);
            BasFunction.ChooseSize(meanOrdinateLeft5, meanOrdinateRight5, "small", out t2);
            SubFunction.InsideLine(imageGreen, (int)t1 - 10, (int)meanOrdinateLeft5-10, (int)middleAperture - 90, (int)middleAperture + 90,out meanOrdinateL6);
            //int[,] arrayIrg = new int[rows, cols];
            // 十一、数据计算
            double leftMiantong = meanOrdinateLeft2 - meanOrdinateLeft1;
            double rightMiantong = meanOrdinateRight2 - meanOrdinateRight1;
            double leftJicaitong = meanOrdinateLeft3 - meanOrdinateLeft2;
            double rightJicaitong = meanOrdinateRight3 - meanOrdinateRight2;
            double leftMian_Jicaitong = meanOrdinateLeft3 - meanOrdinateLeft1;
            double rightMian_Jicaitong = meanOrdinateRight3 - meanOrdinateRight1;
            double shangKongjing = aperture[1] - aperture[0];
            double xiaKongjing = apertureLow[1] - aperture[0];
            double leftKongtong = kongtong[0];
            double rightKongtong = kongtong[1];
            double averAperture = (apertureBegin[0] + apertureEnd[1]) / 2;
            //double kongshen =  curveVertex[0]-middleApertureY;
            double kongdi = meanOrdinateL6 - curveVertex[0];
            double leftKongdiyaoshiliang = meanOrdinateL6 - meanOrdinateLeft4;
            double rightKongdiyaoshiliang = meanOrdinateL6 - meanOrdinateRight4;
            // 十二、数据显示
            double middleLeft = (dataArea[0] + dataArea[1]) / 2;
            double middleRight = (dataArea[2] + dataArea[3]) / 2;
            //左面铜标注
            SubFunction.LineShow(image, (int)middleLeft - 20, (int)meanOrdinateLeft1, (int)middleLeft - 20, (int)meanOrdinateLeft2, "blue");
            SubFunction.LineShow(image, (int)middleLeft - 25, (int)meanOrdinateLeft1, (int)middleLeft - 15, (int)meanOrdinateLeft1, "blue");
            SubFunction.LineShow(image, (int)middleLeft - 25, (int)meanOrdinateLeft2, (int)middleLeft - 15, (int)meanOrdinateLeft2, "blue");
            SubFunction.TextShow(image, leftMiantong * proportion, (int)middleLeft - 20, (int)meanOrdinateLeft2);
            //右面铜标注
            SubFunction.LineShow(image, (int)middleRight + 20, (int)meanOrdinateRight1, (int)middleRight + 20, (int)meanOrdinateRight2, "blue");
            SubFunction.LineShow(image, (int)middleRight + 15, (int)meanOrdinateRight1, (int)middleRight + 25, (int)meanOrdinateRight1, "blue");
            SubFunction.LineShow(image, (int)middleRight + 15, (int)meanOrdinateRight2, (int)middleRight + 25, (int)meanOrdinateRight2, "blue");
            SubFunction.TextShow(image, rightMiantong * proportion, (int)middleRight + 20, (int)meanOrdinateRight2);
            //左基材铜标注
            SubFunction.LineShow(image, (int)middleLeft - 40, (int)meanOrdinateLeft2, (int)middleLeft - 40, (int)meanOrdinateLeft3, "blue");
            SubFunction.LineShow(image, (int)middleLeft - 45, (int)meanOrdinateLeft2, (int)middleLeft - 35, (int)meanOrdinateLeft2, "blue");
            SubFunction.LineShow(image, (int)middleLeft - 45, (int)meanOrdinateLeft3, (int)middleLeft - 35, (int)meanOrdinateLeft3, "blue");
            SubFunction.TextShow(image, leftJicaitong * proportion, (int)middleLeft - 40, (int)meanOrdinateLeft3);
            //右基材铜标注
            SubFunction.LineShow(image, (int)middleRight + 40, (int)meanOrdinateRight2, (int)middleRight + 40, (int)meanOrdinateRight3, "blue");
            SubFunction.LineShow(image, (int)middleRight + 35, (int)meanOrdinateRight2, (int)middleRight + 45, (int)meanOrdinateRight2, "blue");
            SubFunction.LineShow(image, (int)middleRight + 35, (int)meanOrdinateRight3, (int)middleRight + 45, (int)meanOrdinateRight3, "blue");
            SubFunction.TextShow(image, rightJicaitong * proportion, (int)middleRight + 40, (int)meanOrdinateRight3);
            //左面铜＋基材铜标注
            SubFunction.LineShow(image, (int)middleLeft, (int)meanOrdinateLeft1, (int)middleLeft, (int)meanOrdinateLeft3, "blue");
            SubFunction.LineShow(image, (int)middleLeft - 5, (int)meanOrdinateLeft1, (int)middleLeft + 5, (int)meanOrdinateLeft1, "blue");
            SubFunction.LineShow(image, (int)middleLeft - 5, (int)meanOrdinateLeft3, (int)middleLeft + 5, (int)meanOrdinateLeft3, "blue");
            SubFunction.TextShow(image, leftMian_Jicaitong*0.2689, (int)middleLeft, (int)meanOrdinateLeft3+50);
            //右面铜＋基材铜标注
            SubFunction.LineShow(image, (int)middleRight, (int)meanOrdinateRight1, (int)middleRight, (int)meanOrdinateRight3, "blue");
            SubFunction.LineShow(image, (int)middleRight - 5, (int)meanOrdinateRight1, (int)middleRight + 5, (int)meanOrdinateRight1, "blue");
            SubFunction.LineShow(image, (int)middleRight - 5, (int)meanOrdinateRight3, (int)middleRight + 5, (int)meanOrdinateRight3, "blue");
            SubFunction.TextShow(image, rightMian_Jicaitong * 0.2689, (int)middleRight, (int)meanOrdinateRight3+50);
            //上孔径标注
            SubFunction.LineShow(image, (int)aperture[0], (int)meanOrdinateLeft1 - 20, (int)aperture[1], (int)meanOrdinateLeft1-20, "blue");
            SubFunction.LineShow(image, aperture[0], (int)meanOrdinateLeft1 - 25, aperture[0], (int)meanOrdinateLeft1 - 15, "blue");
            SubFunction.LineShow(image, aperture[1], (int)meanOrdinateLeft1 - 25, aperture[1], (int)meanOrdinateLeft1 - 15, "blue");
            SubFunction.TextShow(image, shangKongjing * 0.2689, (int)middleAperture, (int)meanOrdinateLeft1 - 20);
            //下孔径标注
            SubFunction.LineShow(image, (int)apertureLow[0], (int)meanOrdinateLeft5 - 20, (int)apertureLow[1], (int)meanOrdinateLeft5 - 20, "blue");
            SubFunction.LineShow(image, apertureLow[0], (int)meanOrdinateLeft5 - 25, apertureLow[0], (int)meanOrdinateLeft5 - 15, "blue");
            SubFunction.LineShow(image, apertureLow[1], (int)meanOrdinateLeft5 - 25, apertureLow[1], (int)meanOrdinateLeft5 - 15, "blue");
            SubFunction.TextShow(image, xiaKongjing * 0.2689, (int)(apertureLow[0] + apertureLow[1]) / 2, (int)meanOrdinateLeft5 + 50);
            //孔铜标注
            //左
            SubFunction.LineShow(image, (int)aperture[0], (int)meanOrdinateLeft3, pointLeft[1], pointLeft[0], "blue");
            SubFunction.LineShow(image, aperture[0] - 5, (int)meanOrdinateLeft3, aperture[0] + 5, (int)meanOrdinateLeft3, "blue");
            SubFunction.LineShow(image, pointLeft[1] - 5, pointLeft[0], pointLeft[1] + 5, pointLeft[0], "blue");
            SubFunction.TextShow(image, leftKongtong * proportion, aperture[0], (int)meanOrdinateLeft3+20);
            //右
            SubFunction.LineShow(image, aperture[1], (int)meanOrdinateRight3, pointRight[1], pointRight[0], "blue");
            SubFunction.LineShow(image, aperture[1] - 5, (int)meanOrdinateRight3, aperture[1] + 5, (int)meanOrdinateRight3, "blue");
            SubFunction.LineShow(image, pointRight[1] - 5, pointRight[0], pointRight[1] + 5, pointRight[0], "blue");
            SubFunction.TextShow(image, rightKongtong * proportion, aperture[1], (int)meanOrdinateRight3+20);
            //孔深标注(浅盲孔没有孔深)
            //SubFunction.LineShow(image, (int)middleAperture, curveVertex[0], (int)middleAperture, (int)middleApertureY, "blue");
            //SubFunction.LineShow(image, (int)middleAperture - 5, curveVertex[0], (int)middleAperture + 5, curveVertex[0], "blue");
            //SubFunction.LineShow(image, (int)middleAperture - 5, (int)middleApertureY, (int)middleAperture + 5, (int)middleApertureY, "blue");
            //SubFunction.TextShow(image, kongshen * proportion, curveVertex[1], curveVertex[0]);
            //孔底标注
            double middlep = (meanOrdinateL6+meanOrdinateLeft1)/2;
            SubFunction.LineShow(image, curveVertex[1], curveVertex[0], curveVertex[1], (int)meanOrdinateL6, "blue");
            SubFunction.LineShow(image, curveVertex[1] - 5, curveVertex[0], curveVertex[1] + 5, curveVertex[0], "blue");
            SubFunction.LineShow(image, curveVertex[1] - 5, (int)meanOrdinateL6, curveVertex[1] + 5, (int)meanOrdinateL6, "blue");
            SubFunction.TextShow(image, kongdi * proportion, curveVertex[1], (int)middlep);
            //左孔底咬食量
            SubFunction.LineShow(image, (int)middleLeft, (int)meanOrdinateLeft4, (int)middleLeft, (int)meanOrdinateL6, "blue");
            SubFunction.LineShow(image, (int)middleLeft - 5, (int)meanOrdinateLeft4, (int)middleLeft + 5, (int)meanOrdinateLeft4, "blue");
            SubFunction.LineShow(image, (int)middleLeft - 5, (int)meanOrdinateL6, (int)middleLeft + 5, (int)meanOrdinateL6, "blue");
            SubFunction.TextShow(image, leftKongdiyaoshiliang * proportion, (int)middleLeft, (int)meanOrdinateL6);
            //右孔底咬食量
            SubFunction.LineShow(image, (int)middleRight, (int)meanOrdinateRight4, (int)middleRight, (int)meanOrdinateL6, "blue");
            SubFunction.LineShow(image, (int)middleRight - 5, (int)meanOrdinateRight4, (int)middleRight + 5, (int)meanOrdinateRight4, "blue");
            SubFunction.LineShow(image, (int)middleRight - 5, (int)meanOrdinateL6, (int)middleRight + 5, (int)meanOrdinateL6, "blue");
            SubFunction.TextShow(image, rightKongdiyaoshiliang * proportion, (int)middleRight, (int)meanOrdinateL6);

            //拟合
            SubFunction.LineShow(image, apertureLow[0], (int)meanOrdinateL6, apertureLow[1], (int)meanOrdinateL6);
            SubFunction.LineShow(image, dataArea[0], (int)meanOrdinateLeft2, dataArea[1], (int)meanOrdinateLeft2);
            SubFunction.LineShow(image, dataArea[2], (int)meanOrdinateRight2, dataArea[3], (int)meanOrdinateRight2);
            // 保存
            //Cv2.ImWrite(@"D:\eshi.jpg",image);
            // 显示
            new Window("demo1", WindowMode.Normal, image);
            Cv2.WaitKey(0); 
        }
        public static void ShuangcengShenmangkong(string fileName)
        {
            // 获取图片
            Mat image = new Mat(fileName, ImreadModes.Color);

            // 转换为灰度图
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);

            // 二值化，获得目标区域
            Mat imageContour = imageGray.Threshold(0, 255, ThresholdTypes.Otsu);

            // 转换成数组
            int[,] arrayContour = BasFunction.Mat2Array(imageContour);
            arrayContour = BasFunction.ConversionRange(arrayContour);

            // 寻找两层分界点
            int[] sum = BasFunction.Sum(arrayContour, 2);// 每行求和
            int y1 = 0;// 上区域开始
            int y2 = 0;// 上区域结束
            int y3 = 0;// 下区域结束
            int y4 = 0;// 下区域开始
            for (int i = 0; i < imageContour.Rows; i++)
            {
                if (sum[i] > 0)
                {
                    y1 = i;
                    break;
                }
            }
            for (int i = imageContour.Rows - 1; i > 0; i--)
            {
                if (sum[i] > 0)
                {
                    y4 = i;
                    break;
                }
            }
            int[] newSum = BasFunction.Intercept(sum, y1, y4);
            int min = BasFunction.Min(newSum);
            for (int i = y1; i < y4; i++)
            {
                if (sum[i] < min + 50)
                {
                    y2 = i;
                    break;
                }
            }
            for (int i = y4; i > y2; i--)
            {
                if (sum[i] < min + 50)
                {
                    y3 = i;
                    break;
                }
            }
            int middle = (y2 + y3) / 2;// 分界点

            // 分成两份
            // 分原图
            Mat image1 = new Mat();
            Mat image2 = new Mat();
            BasFunction.InterceptMat(image, out image1, 0, middle, 0, image.Cols);
            BasFunction.InterceptMat(image, out image2, middle, image.Rows, 0, image.Cols);

            // 重新阈值分割
            Mat imageContour1 = image1.Threshold(0, 255, ThresholdTypes.Otsu);
            Mat imageContour2 = image2.Threshold(0, 255, ThresholdTypes.Otsu);

            // 对分好的图进行边缘检测
            Mat imageOutline1 = new Mat();
            Mat imageOutline2 = new Mat();
            SubFunction.Sobel(imageContour1, out imageOutline1);
            SubFunction.Sobel(imageContour2, out imageOutline2);

            // 对下方的图进行180度旋转
            Cv2.Flip(imageContour2, imageContour2, FlipMode.X);
            Cv2.Flip(imageOutline2, imageOutline2, FlipMode.X);

            // 调用
            Mat result1 = new Mat();
            Mat result2 = new Mat();
            DrawShenmangkong(image, out result1, imageContour1, imageOutline1);
            DrawShenmangkong2(result1, out result2, imageContour2, imageOutline2,middle);
        }
        public static void DancengShenmangkong(string fileName)
        {
            // 获取图片
            Mat image = new Mat(fileName, ImreadModes.Color);

            // 转换为灰度图
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);

            // 二值化，获得目标区域
            Mat imageContour = imageGray.Threshold(0, 255, ThresholdTypes.Otsu);

            // 闭运算，填充孔洞
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Close, se);

            // 边缘检测
            Mat imageOutline = new Mat();
            SubFunction.Sobel(imageContour, out imageOutline);

            // 调用计算程序
            Mat result = new Mat();
            DrawShenmangkong(image, out result, imageContour, imageOutline);
        }
        public static void DrawShenmangkong(Mat image, out Mat result,Mat imageContour,Mat imageOutline)
        {
            // 一、预处理部分
            // 像素实际比例
            double proportion = 0.2689;

            // 得到行列数
            int rows = image.Rows;
            int cols = image.Cols;
            // 转换成灰度图
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);
            // 获得蓝色，绿色，红色通道图片
            Mat imageBlue, imageGreen, imageRed = new Mat(imageGray.Size(), imageGray.Type());
            SubFunction.SeparateRGB(image, out imageBlue, out imageGreen, out imageRed);
            // 将Mat类转换成数组
            int[,] arrayOutline = BasFunction.Mat2Array(imageOutline);
            arrayOutline = BasFunction.ConversionRange(arrayOutline);//将数组转为0，1数组

            int[,] arrayContour = BasFunction.Mat2Array(imageContour);
            arrayContour = BasFunction.ConversionRange(arrayContour);

            // 二、计算中部区域的边界，middleArea[0]中部左边界，middleArea[1]中部右边界
            int[] middleArea = SubFunction.GetMiddleArea(imageContour);

            // 三、计算左右边界
            //dataArea[0]左部分左边界，dataArea[1]左部分右边界，dataArea[2]右部分左边界，dataArea[3]右部分右边界
            int[] dataArea = SubFunction.GetDataArea(imageContour, middleArea);

            // 四、提取L1，L3            
            double meanOrdinateLeft1 = 0;// L1左部分纵坐标
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateLeft1, dataArea[0], dataArea[1]);
            
            double meanOrdinateRight1 = 0;// L1右部分纵坐标
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateRight1, dataArea[2], dataArea[3]);
            
            double meanOrdinateLeft3 = 0;// L3左部分纵坐标
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateLeft3, dataArea[0], dataArea[1], meanOrdinateLeft1);
            
            double meanOrdinateRight3 = 0;// L3右部分纵坐标
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateRight3, dataArea[2], dataArea[3], meanOrdinateRight1);

            // 五、提取内部线L2
            double meanOrdinateLeft2 = 0;
            double meanOrdinateRight2 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateLeft1 + 10, (int)meanOrdinateLeft3 - 10, dataArea[0], dataArea[1], out meanOrdinateLeft2);
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateRight1 + 10, (int)meanOrdinateRight3 - 10, dataArea[2], dataArea[3], out meanOrdinateRight2);

            // 六、提取L5，L6
            // 对轮廓线腐蚀
            Mat seErode = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 1));// 结构元素
            Mat imageOutlineErode = new Mat();// 腐蚀后轮廓线
            Cv2.Erode(imageOutline, imageOutlineErode, seErode);// 腐蚀
            
            // 转换成数组            
            int[,] arrayOutlineErode = BasFunction.Mat2Array(imageOutlineErode);// 将Mat类转换成数组           
            arrayOutlineErode = BasFunction.ConversionRange(arrayOutlineErode);//将数组转为0，1数组

            // 提取
            double meanOrdinateLeft5 = 0;// L5左部分
            SubFunction.ExtractLines(arrayOutlineErode, out meanOrdinateLeft5, dataArea[0], dataArea[1]-50,meanOrdinateLeft3);

            double meanOrdinateRight5 = 0;// L5右部分
            SubFunction.ExtractLines(arrayOutlineErode, out meanOrdinateRight5, dataArea[2]+50, dataArea[3], meanOrdinateRight3);

            double meanOrdinateLeft6 = 0;// L6左部分
            SubFunction.ExtractLines(arrayOutlineErode, out meanOrdinateLeft6, dataArea[0], dataArea[1], meanOrdinateLeft5);

            double meanOrdinateRight6 = 0;// L6右部分
            SubFunction.ExtractLines(arrayOutlineErode, out meanOrdinateRight6, dataArea[2], dataArea[3], meanOrdinateRight5);

            // 七、提取胶体线
            Mat glue = new Mat();
            SubFunction.GlueArea(imageContour, imageRed, out glue, (int)meanOrdinateLeft3, (int)meanOrdinateLeft5,0,cols);

            // 转为数组
            int[,] arrayGlue = BasFunction.Mat2Array(glue);
            arrayGlue = BasFunction.ConversionRange(arrayGlue);

            // 八、提取L4
            double meanOrdinateLeft4 = 0;// L4左部分
            SubFunction.ExtractLines2(arrayGlue, out meanOrdinateLeft4, dataArea[0], dataArea[1]-50, meanOrdinateLeft5);

            double meanOrdinateRight4 = 0;// L4左部分
            SubFunction.ExtractLines2(arrayGlue, out meanOrdinateRight4, dataArea[2]+50, dataArea[3] , meanOrdinateRight5);
           
            // 九、计算孔径起止点
            //aperture[0]孔径起始点（左）；aperture[1]孔径起始点（右）
            int[] aperture = new int[2];
            SubFunction.GetAperture(arrayContour, out aperture, (int)meanOrdinateLeft3, (int)meanOrdinateRight3, middleArea, dataArea);
            
            int[] apertureBegin = { (int)meanOrdinateLeft3, aperture[0] };// 孔径左边左边
            int[] apertureEnd = { (int)meanOrdinateRight3, aperture[1] };// 孔径右边左边
            
            double middleAperture = (aperture[0] + aperture[1]) / 2;//孔径中点

            // 十、计算孔铜
            // 得到曲面线条L1
            int[,] line1 = new int[rows, cols];           
            double averageCoordinate1 = 0;//L1的纵坐标            
            SubFunction.ExtractLines(arrayOutline, out line1, out averageCoordinate1, dataArea[0], dataArea[3]);
            
             //求孔径起始点与曲面之间的最短距离，以及最短距离时的曲面坐标
            double[] kongtong = new double[2];
            int[] pointLeft = new int[2];
            int[] pointRight = new int[2];
            SubFunction.GetKongtong(line1, apertureBegin, apertureEnd, out kongtong, out pointLeft, out pointRight);

            // 十一、计算胶内缩
            // 上胶边界
            int[] upperWaist = new int[2];
            SubFunction.GetWaist(imageContour, out upperWaist, (int)meanOrdinateLeft4 - 30, (int)meanOrdinateLeft4 + 30, (int)middleAperture);

            // 下胶边界
            int[] lowerWaist = new int[2];
            SubFunction.GetLowerWaist(imageContour, out lowerWaist, (int)meanOrdinateLeft4, (int)meanOrdinateLeft5, dataArea);

            // 十二 、提取L7
            double meanOrdinateL7 = 0;
            double t1 = 0;
            BasFunction.ChooseSize(meanOrdinateLeft5, meanOrdinateRight5, "small",out t1);           
            SubFunction.InsideLine(imageGreen, (int)t1 - 10, (int)meanOrdinateLeft6 - 10, (int)middleAperture - 90, (int)middleAperture + 90, out meanOrdinateL7);

            // 十三、下孔径(这里用的是和上孔径一样的行数，但是上下边界的问题可能会有，需要注意)
            int[] lowerAperture = new int[2];
            SubFunction.GetAperture(arrayContour, out lowerAperture, (int)meanOrdinateLeft5, (int)meanOrdinateRight5, middleArea, dataArea);

            // 十四、曲面最凸点坐标           
            int[] curveVertex = new int[2];           
            double middleApertureY;//孔径平均高度
            SubFunction.CurveVertex(line1, apertureBegin, apertureEnd, out curveVertex, out middleApertureY);

            // 十五、计算
            double leftMiantong = meanOrdinateLeft2 - meanOrdinateLeft1;
            double rightMiantong = meanOrdinateRight2 - meanOrdinateRight1;
            double leftJicaitong = meanOrdinateLeft3 - meanOrdinateLeft2;
            double rightJicaitong = meanOrdinateRight3 - meanOrdinateRight2;
            double leftMian_Jicaitong = meanOrdinateLeft3 - meanOrdinateLeft1;
            double rightMian_Jicaitong = meanOrdinateRight3 - meanOrdinateRight1;
            double leftJiaohou = meanOrdinateLeft5 - meanOrdinateLeft4;
            double rightJiaohou = meanOrdinateRight5 - meanOrdinateRight4;
            double leftKongdiyaoshiliang = meanOrdinateL7 - meanOrdinateLeft5;
            double rightKongdiyaoshiliang = meanOrdinateL7 - meanOrdinateRight5;
            double leftJiaoneisuo = upperWaist[0] - lowerWaist[0];
            double rightJiaoneisuo = lowerWaist[1] - upperWaist[1];
            double leftKongtong = kongtong[0];
            double rightKongtong = kongtong[1];
            double upperKongjing = aperture[1] - aperture[0];
            double lowerKongjing = lowerAperture[1] - lowerAperture[0];
            double kongshen = curveVertex[0] - middleApertureY;
            double kongdi = meanOrdinateL7 - curveVertex[0];

            // 十六、标记
            double middleLeft = (dataArea[0] + dataArea[1]) / 2;
            double middleRight = (dataArea[2] + dataArea[3]) / 2;
            // 左面铜
            SubFunction.LabelVertical(image, (int)middleLeft-20, (int)meanOrdinateLeft1, (int)middleLeft-20, (int)meanOrdinateLeft2, leftMiantong);
            // 右面铜
            SubFunction.LabelVertical(image, (int)middleRight+20, (int)meanOrdinateRight1, (int)middleRight+20, (int)meanOrdinateRight2, rightMiantong);
            // 左基材铜
            SubFunction.LabelVertical(image, (int)middleLeft - 40, (int)meanOrdinateLeft2, (int)middleLeft - 40, (int)meanOrdinateLeft3, leftJicaitong);
            // 右基材铜
            SubFunction.LabelVertical(image, (int)middleRight + 40, (int)meanOrdinateRight2, (int)middleRight + 40, (int)meanOrdinateRight3, rightJicaitong);
            // 左面铜+基材铜
            SubFunction.LabelVertical(image, (int)middleLeft, (int)meanOrdinateLeft1, (int)middleLeft, (int)meanOrdinateLeft3, leftMian_Jicaitong);
            // 右面铜+基材铜
            SubFunction.LabelVertical(image, (int)middleRight, (int)meanOrdinateRight1, (int)middleRight, (int)meanOrdinateRight3, rightMian_Jicaitong);
            // 左胶厚
            SubFunction.LabelVertical(image, (int)middleLeft, (int)meanOrdinateLeft4, (int)middleLeft, (int)meanOrdinateLeft5, leftJiaohou);
            // 右胶厚
            SubFunction.LabelVertical(image, (int)middleRight, (int)meanOrdinateRight4, (int)middleRight, (int)meanOrdinateRight5, rightJiaohou);
            // 左孔底咬食量
            SubFunction.LabelVertical(image, (int)middleLeft, (int)meanOrdinateLeft5, (int)middleLeft, (int)meanOrdinateL7, leftKongdiyaoshiliang);
            // 右孔底咬食量
            SubFunction.LabelVertical(image, (int)middleRight, (int)meanOrdinateRight5, (int)middleRight, (int)meanOrdinateL7, rightKongdiyaoshiliang);
            // 左胶内缩
            SubFunction.LableHorizontal(image, lowerWaist[0], (int)meanOrdinateLeft4, upperWaist[0], (int)meanOrdinateLeft4, leftJiaoneisuo);
            // 右胶内缩
            SubFunction.LableHorizontal(image, upperWaist[1], (int)meanOrdinateRight4, lowerWaist[1], (int)meanOrdinateRight4, rightJiaoneisuo);
            // 左孔铜
            SubFunction.LabelVertical(image, apertureBegin[1], apertureBegin[0], pointLeft[1], pointLeft[0], leftKongtong);
            // 右孔铜
            SubFunction.LabelVertical(image, apertureEnd[1], apertureEnd[0], pointRight[1], pointRight[0], rightKongtong);
            // 上孔径
            SubFunction.LableHorizontal(image, apertureBegin[1], (int)meanOrdinateLeft1 - 30, apertureEnd[1], (int)meanOrdinateLeft1 - 30, upperKongjing);
            // 下孔径
            SubFunction.LableHorizontal(image, lowerAperture[0], (int)meanOrdinateL7 + 20, lowerAperture[1], (int)meanOrdinateL7 + 20, lowerKongjing);
            // 孔深
            SubFunction.LabelVertical(image, curveVertex[1], curveVertex[0], curveVertex[1], (int)middleApertureY, kongshen);
            // 孔底
            SubFunction.LabelVertical(image, curveVertex[1], curveVertex[0], curveVertex[1], (int)meanOrdinateL7, kongdi);

            result = image;
        }
        public static void DrawShenmangkong2(Mat image, out Mat result, Mat imageContour, Mat imageOutline,int middle)
        {
            // 一、预处理部分
            // 像素实际比例
            double proportion = 0.2689;

            // 得到行列数
            int rows = image.Rows;
            int cols = image.Cols;
            // 转换成灰度图
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);
            // 获得蓝色，绿色，红色通道图片
            Mat imageBlue, imageGreen, imageRed = new Mat(imageGray.Size(), imageGray.Type());
            SubFunction.SeparateRGB(image, out imageBlue, out imageGreen, out imageRed);
            // 将Mat类转换成数组
            int[,] arrayOutline = BasFunction.Mat2Array(imageOutline);
            arrayOutline = BasFunction.ConversionRange(arrayOutline);//将数组转为0，1数组

            int[,] arrayContour = BasFunction.Mat2Array(imageContour);
            arrayContour = BasFunction.ConversionRange(arrayContour);

            // 二、计算中部区域的边界，middleArea[0]中部左边界，middleArea[1]中部右边界
            int[] middleArea = SubFunction.GetMiddleArea(imageContour);

            // 三、计算左右边界
            //dataArea[0]左部分左边界，dataArea[1]左部分右边界，dataArea[2]右部分左边界，dataArea[3]右部分右边界
            int[] dataArea = SubFunction.GetDataArea(imageContour, middleArea);

            // 四、提取L1，L3            
            double meanOrdinateLeft1 = 0;// L1左部分纵坐标
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateLeft1, dataArea[0], dataArea[1]);

            double meanOrdinateRight1 = 0;// L1右部分纵坐标
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateRight1, dataArea[2], dataArea[3]);

            double meanOrdinateLeft3 = 0;// L3左部分纵坐标
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateLeft3, dataArea[0], dataArea[1], meanOrdinateLeft1);

            double meanOrdinateRight3 = 0;// L3右部分纵坐标
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateRight3, dataArea[2], dataArea[3], meanOrdinateRight1);

            // 五、提取内部线L2
            double meanOrdinateLeft2 = 0;
            double meanOrdinateRight2 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateLeft1 + 10, (int)meanOrdinateLeft3 - 10, dataArea[0], dataArea[1], out meanOrdinateLeft2);
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateRight1 + 10, (int)meanOrdinateRight3 - 10, dataArea[2], dataArea[3], out meanOrdinateRight2);

            // 六、提取L5，L6
            // 对轮廓线腐蚀
            Mat seErode = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 1));// 结构元素
            Mat imageOutlineErode = new Mat();// 腐蚀后轮廓线
            Cv2.Erode(imageOutline, imageOutlineErode, seErode);// 腐蚀

            // 转换成数组            
            int[,] arrayOutlineErode = BasFunction.Mat2Array(imageOutlineErode);// 将Mat类转换成数组           
            arrayOutlineErode = BasFunction.ConversionRange(arrayOutlineErode);//将数组转为0，1数组

            // 提取
            double meanOrdinateLeft5 = 0;// L5左部分
            SubFunction.ExtractLines(arrayOutlineErode, out meanOrdinateLeft5, dataArea[0], dataArea[1] - 50, meanOrdinateLeft3);

            double meanOrdinateRight5 = 0;// L5右部分
            SubFunction.ExtractLines(arrayOutlineErode, out meanOrdinateRight5, dataArea[2] + 50, dataArea[3], meanOrdinateRight3);

            double meanOrdinateLeft6 = 0;// L6左部分
            SubFunction.ExtractLines(arrayOutlineErode, out meanOrdinateLeft6, dataArea[0], dataArea[1], meanOrdinateLeft5);

            double meanOrdinateRight6 = 0;// L6右部分
            SubFunction.ExtractLines(arrayOutlineErode, out meanOrdinateRight6, dataArea[2], dataArea[3], meanOrdinateRight5);

            // 七、提取胶体线
            Mat glue = new Mat();
            SubFunction.GlueArea(imageContour, imageRed, out glue, (int)meanOrdinateLeft3, (int)meanOrdinateLeft5,0,cols);

            // 转为数组
            int[,] arrayGlue = BasFunction.Mat2Array(glue);
            arrayGlue = BasFunction.ConversionRange(arrayGlue);

            // 八、提取L4
            double meanOrdinateLeft4 = 0;// L4左部分
            SubFunction.ExtractLines2(arrayGlue, out meanOrdinateLeft4, dataArea[0], dataArea[1] - 50, meanOrdinateLeft5);

            double meanOrdinateRight4 = 0;// L4左部分
            SubFunction.ExtractLines2(arrayGlue, out meanOrdinateRight4, dataArea[2] + 50, dataArea[3], meanOrdinateRight5);

            // 九、计算孔径起止点
            //aperture[0]孔径起始点（左）；aperture[1]孔径起始点（右）
            int[] aperture = new int[2];
            SubFunction.GetAperture(arrayContour, out aperture, (int)meanOrdinateLeft3, (int)meanOrdinateRight3, middleArea, dataArea);

            int[] apertureBegin = { (int)meanOrdinateLeft3, aperture[0] };// 孔径左边左边
            int[] apertureEnd = { (int)meanOrdinateRight3, aperture[1] };// 孔径右边左边

            double middleAperture = (aperture[0] + aperture[1]) / 2;//孔径中点

            // 十、计算孔铜
            // 得到曲面线条L1
            int[,] line1 = new int[rows, cols];
            double averageCoordinate1 = 0;//L1的纵坐标            
            SubFunction.ExtractLines(arrayOutline, out line1, out averageCoordinate1, dataArea[0], dataArea[3]);

            //求孔径起始点与曲面之间的最短距离，以及最短距离时的曲面坐标
            double[] kongtong = new double[2];
            int[] pointLeft = new int[2];
            int[] pointRight = new int[2];
            SubFunction.GetKongtong(line1, apertureBegin, apertureEnd, out kongtong, out pointLeft, out pointRight);

            // 十一、计算胶内缩
            // 上胶边界
            int[] upperWaist = new int[2];
            SubFunction.GetWaist(imageContour, out upperWaist, (int)meanOrdinateLeft4 - 30, (int)meanOrdinateLeft4 + 30, (int)middleAperture);

            // 下胶边界
            int[] lowerWaist = new int[2];
            SubFunction.GetLowerWaist(imageContour, out lowerWaist, (int)meanOrdinateLeft4, (int)meanOrdinateLeft5, dataArea);

            // 十二 、提取L7
            double meanOrdinateL7 = 0;
            double t1 = 0;
            BasFunction.ChooseSize(meanOrdinateLeft5, meanOrdinateRight5, "small", out t1);
            SubFunction.InsideLine(imageGreen, (int)t1 - 10, (int)meanOrdinateLeft6 - 10, (int)middleAperture - 90, (int)middleAperture + 90, out meanOrdinateL7);

            // 十三、下孔径(这里用的是和上孔径一样的行数，但是上下边界的问题可能会有，需要注意)
            int[] lowerAperture = new int[2];
            SubFunction.GetAperture(arrayContour, out lowerAperture, (int)meanOrdinateLeft5, (int)meanOrdinateRight5, middleArea, dataArea);

            // 十四、曲面最凸点坐标           
            int[] curveVertex = new int[2];
            double middleApertureY;//孔径平均高度
            SubFunction.CurveVertex(line1, apertureBegin, apertureEnd, out curveVertex, out middleApertureY);

            // 十五、计算
            double leftMiantong = meanOrdinateLeft2 - meanOrdinateLeft1;
            double rightMiantong = meanOrdinateRight2 - meanOrdinateRight1;
            double leftJicaitong = meanOrdinateLeft3 - meanOrdinateLeft2;
            double rightJicaitong = meanOrdinateRight3 - meanOrdinateRight2;
            double leftMian_Jicaitong = meanOrdinateLeft3 - meanOrdinateLeft1;
            double rightMian_Jicaitong = meanOrdinateRight3 - meanOrdinateRight1;
            double leftJiaohou = meanOrdinateLeft5 - meanOrdinateLeft4;
            double rightJiaohou = meanOrdinateRight5 - meanOrdinateRight4;
            double leftKongdiyaoshiliang = meanOrdinateL7 - meanOrdinateLeft5;
            double rightKongdiyaoshiliang = meanOrdinateL7 - meanOrdinateRight5;
            double leftJiaoneisuo = upperWaist[0] - lowerWaist[0];
            double rightJiaoneisuo = lowerWaist[1] - upperWaist[1];
            double leftKongtong = kongtong[0];
            double rightKongtong = kongtong[1];
            double upperKongjing = aperture[1] - aperture[0];
            double lowerKongjing = lowerAperture[1] - lowerAperture[0];
            double kongshen = curveVertex[0] - middleApertureY;
            double kongdi = meanOrdinateL7 - curveVertex[0];

            // 十六、标记
            double middleLeft = (dataArea[0] + dataArea[1]) / 2;
            double middleRight = (dataArea[2] + dataArea[3]) / 2;
            // 左面铜
            SubFunction.LabelVertical(image, (int)middleLeft - 20, (int)(2*middle-meanOrdinateLeft1), (int)middleLeft - 20, (int)(2 * middle - meanOrdinateLeft2), leftMiantong);
            // 右面铜
            SubFunction.LabelVertical(image, (int)middleRight + 20, (int)(2 * middle - meanOrdinateRight1), (int)middleRight + 20, (int)(2 * middle - meanOrdinateRight2), rightMiantong);
            // 左基材铜
            SubFunction.LabelVertical(image, (int)middleLeft - 40, (int)(2 * middle - meanOrdinateLeft2), (int)middleLeft - 40, (int)(2 * middle - meanOrdinateLeft3), leftJicaitong);
            // 右基材铜
            SubFunction.LabelVertical(image, (int)middleRight + 40, (int)(2 * middle - meanOrdinateRight2), (int)middleRight + 40, (int)(2 * middle - meanOrdinateRight3), rightJicaitong);
            // 左面铜+基材铜
            SubFunction.LabelVertical(image, (int)middleLeft, (int)(2 * middle - meanOrdinateLeft1), (int)middleLeft, (int)(2 * middle - meanOrdinateLeft3), leftMian_Jicaitong);
            // 右面铜+基材铜
            SubFunction.LabelVertical(image, (int)middleRight, (int)(2 * middle - meanOrdinateRight1), (int)middleRight, (int)(2 * middle - meanOrdinateRight3), rightMian_Jicaitong);
            // 左胶厚
            SubFunction.LabelVertical(image, (int)middleLeft, (int)(2 * middle - meanOrdinateLeft4), (int)middleLeft, (int)(2 * middle - meanOrdinateLeft5), leftJiaohou);
            // 右胶厚
            SubFunction.LabelVertical(image, (int)middleRight, (int)(2 * middle - meanOrdinateRight4), (int)middleRight, (int)(2 * middle - meanOrdinateRight5), rightJiaohou);
            // 左孔底咬食量
            SubFunction.LabelVertical(image, (int)middleLeft, (int)(2 * middle - meanOrdinateLeft5), (int)middleLeft, (int)(2 * middle - meanOrdinateL7), leftKongdiyaoshiliang);
            // 右孔底咬食量
            SubFunction.LabelVertical(image, (int)middleRight, (int)(2 * middle - meanOrdinateRight5), (int)middleRight, (int)(2 * middle - meanOrdinateL7), rightKongdiyaoshiliang);
            // 左胶内缩
            SubFunction.LableHorizontal(image, lowerWaist[0], (int)(2 * middle - meanOrdinateLeft4), upperWaist[0], (int)(2 * middle - meanOrdinateLeft4), leftJiaoneisuo);
            // 右胶内缩
            SubFunction.LableHorizontal(image, upperWaist[1], (int)(2 * middle - meanOrdinateRight4), lowerWaist[1], (int)(2 * middle - meanOrdinateRight4), rightJiaoneisuo);
            // 左孔铜
            SubFunction.LabelVertical(image, apertureBegin[1], (2 * middle - apertureBegin[0]), pointLeft[1], (2 * middle - pointLeft[0]), leftKongtong);
            // 右孔铜
            SubFunction.LabelVertical(image, apertureEnd[1], (2 * middle - apertureEnd[0]), pointRight[1], (2 * middle - pointRight[0]), rightKongtong);
            // 上孔径
            SubFunction.LableHorizontal(image, apertureBegin[1], (int)(2 * middle - (meanOrdinateLeft1 - 30)), apertureEnd[1], (int)(2 * middle - (meanOrdinateLeft1 - 30)), upperKongjing);
            // 下孔径
            SubFunction.LableHorizontal(image, lowerAperture[0], (int)(2 * middle - (meanOrdinateL7 + 20)), lowerAperture[1], (int)(2 * middle - (meanOrdinateL7 + 20)), lowerKongjing);
            // 孔深
            SubFunction.LabelVertical(image, curveVertex[1], curveVertex[0], curveVertex[1], (int)(2 * middle - middleApertureY), kongshen);
            // 孔底
            SubFunction.LabelVertical(image, curveVertex[1], curveVertex[0], curveVertex[1], (int)(2 * middle - meanOrdinateL7), kongdi);

            result = image;
        }
        public static void CaokongShuangcengYou(string fileName)
        {
            // 一、预处理
            // 读取图片
            Mat image = new Mat(fileName, ImreadModes.Color);

            //获取图片的长宽
            int rows = image.Rows;
            int cols = image.Cols;

            // 转换为灰度图
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);

            //获得蓝色，绿色，红色通道图片
            Mat imageBlue, imageGreen, imageRed = new Mat(imageGray.Size(), imageGray.Type());
            SubFunction.SeparateRGB(image, out imageBlue, out imageGreen, out imageRed);

            // 二值化，获得目标区域
            Mat imageContour = imageGray.Threshold(0, 255, ThresholdTypes.Otsu);
            // 闭运算，消除小孔
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));// 结构元素
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Close, se);

            // 转成数组
            int[,] arrayContour = BasFunction.Mat2Array(imageContour);
            arrayContour = BasFunction.ConversionRange(arrayContour);

            // 去亮光
            int b2, b3;
            SubFunction.SplitArea(arrayContour, out b2, out b3);
            if ((b3 - b2) > 100)
            {
                Mat result = new Mat();
                BasFunction.SetNumber(imageContour, out result, 0, rows, 0, b3, 0);// 亮光区域置0
                imageContour = result;
            }

            // 边缘检测
            Mat imageOutlint = new Mat();
            SubFunction.Sobel(imageContour, out imageOutlint);

            int[,] arrayOutline = BasFunction.Mat2Array(imageOutlint);
            arrayOutline = BasFunction.ConversionRange(arrayOutline);

            // 二、计算数据提取区域
            // 对图片进行填充 
            Mat imageFill = new Mat();
            SubFunction.Fill(imageContour, out imageFill);

            // 计算数据提取区域
            int[] dataArea = new int[2];
            SubFunction.DataArea2(imageFill, out dataArea);

            // 三、提取L1，L3，L4，L6
            double meanOrdinateL1 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL1, dataArea[0], dataArea[1]);
            double meanOrdinateL3 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL3, dataArea[0], dataArea[1],meanOrdinateL1);
            double meanOrdinateL4 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL4, dataArea[0], dataArea[1], meanOrdinateL3);
            double meanOrdinateL6 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL6, dataArea[0], dataArea[1], meanOrdinateL4);

            // 四、提取L2
            double meanOrdinateL2 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateL1 + 10, (int)meanOrdinateL3 - 10, dataArea[0], dataArea[1], out meanOrdinateL2);

            // 五、提取L5
            double meanOrdinateL5 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateL4 + 10, (int)meanOrdinateL6 - 10, dataArea[0], dataArea[1], out meanOrdinateL5);

            // 六、提竖线V1,V2
            double abscissaV1 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline, out abscissaV1, (int)meanOrdinateL3, (int)meanOrdinateL4);
            double abscissaV2 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline, out abscissaV2, (int)meanOrdinateL3, (int)meanOrdinateL4, abscissaV1);

            // 七、数据计算
            double upperMiantong = meanOrdinateL2 - meanOrdinateL1;
            double upperJicaitong = meanOrdinateL3 - meanOrdinateL2;
            double upperMian_Jicaitong = meanOrdinateL3 - meanOrdinateL1;
            double lowerMiantong = meanOrdinateL6 - meanOrdinateL5;
            double lowerJicaitong = meanOrdinateL5 - meanOrdinateL4;
            double lowerMian_Jicaitong = meanOrdinateL6 - meanOrdinateL4;
            double kongtong = abscissaV2 - abscissaV1;

            // 八、标记
            int middle = (dataArea[0] + dataArea[1]) / 2;
            int middle2 = (int)((meanOrdinateL3 + meanOrdinateL4) / 2);
            // 上面铜
            SubFunction.LabelVertical(image, middle + 40, (int)meanOrdinateL1, middle + 40, (int)meanOrdinateL2,upperMiantong);
            // 上基材铜
            SubFunction.LabelVertical(image, middle - 40, (int)meanOrdinateL2, middle - 40, (int)meanOrdinateL3, upperJicaitong);
            // 上面铜+基材铜
            SubFunction.LabelVertical(image, middle, (int)meanOrdinateL1, middle, (int)meanOrdinateL3, upperMian_Jicaitong);
            // 下面铜
            SubFunction.LabelVertical(image, middle + 40, (int)meanOrdinateL5, middle + 40, (int)meanOrdinateL6, lowerMiantong);
            // 下基材铜
            SubFunction.LabelVertical(image, middle - 40, (int)meanOrdinateL4, middle - 40, (int)meanOrdinateL5, lowerJicaitong);
            // 下面铜+基材铜
            SubFunction.LabelVertical(image, middle, (int)meanOrdinateL4, middle, (int)meanOrdinateL6, lowerMian_Jicaitong);
            // 孔铜
            SubFunction.LableHorizontal(image, (int)abscissaV2, middle2, (int)abscissaV1, middle2, kongtong);
        }
        public static void CaokongShuangcengZuo(string fileName)
        {
            // 一、预处理
            // 读取图片
            Mat image = new Mat(fileName, ImreadModes.Color);

            //获取图片的长宽
            int rows = image.Rows;
            int cols = image.Cols;

            // 转换为灰度图
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);

            //获得蓝色，绿色，红色通道图片
            Mat imageBlue, imageGreen, imageRed = new Mat(imageGray.Size(), imageGray.Type());
            SubFunction.SeparateRGB(image, out imageBlue, out imageGreen, out imageRed);

            // 二值化，获得目标区域
            Mat imageContour = imageGray.Threshold(0, 255, ThresholdTypes.Otsu);
            // 闭运算，消除小孔
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));// 结构元素
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Close, se);

            // 转成数组
            int[,] arrayContour = BasFunction.Mat2Array(imageContour);
            arrayContour = BasFunction.ConversionRange(arrayContour);

            // 去亮光
            int b2, b3;
            SubFunction.SplitArea(arrayContour, out b2, out b3);
            if ((b3 - b2) > 100)
            {
                Mat result = new Mat();
                BasFunction.SetNumber(imageContour, out result, 0, rows, b2, cols, 0);// 亮光区域置0
                imageContour = result;
            }

            // 边缘检测
            Mat imageOutlint = new Mat();
            SubFunction.Sobel(imageContour, out imageOutlint);

            int[,] arrayOutline = BasFunction.Mat2Array(imageOutlint);
            arrayOutline = BasFunction.ConversionRange(arrayOutline);

            // 二、计算数据提取区域
            // 对图片进行填充 
            Mat imageFill = new Mat();
            SubFunction.Fill(imageContour, out imageFill);

            // 计算数据提取区域
            int[] dataArea = new int[2];
            SubFunction.DataArea2(imageFill, out dataArea);

            // 三、提取L1，L3，L4，L6
            double meanOrdinateL1 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL1, dataArea[0], dataArea[1]);
            double meanOrdinateL3 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL3, dataArea[0], dataArea[1], meanOrdinateL1);
            double meanOrdinateL4 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL4, dataArea[0], dataArea[1], meanOrdinateL3);
            double meanOrdinateL6 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL6, dataArea[0], dataArea[1], meanOrdinateL4);

            // 四、提取L2
            double meanOrdinateL2 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateL1 + 10, (int)meanOrdinateL3 - 10, dataArea[0], dataArea[1], out meanOrdinateL2);

            // 五、提取L5
            double meanOrdinateL5 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateL4 + 10, (int)meanOrdinateL6 - 10, dataArea[0], dataArea[1], out meanOrdinateL5);

            // 六、提竖线V1,V2
            double abscissaV1 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline, out abscissaV1, (int)meanOrdinateL3, (int)meanOrdinateL4);
            double abscissaV2 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline, out abscissaV2, (int)meanOrdinateL3, (int)meanOrdinateL4, abscissaV1);

            // 七、数据计算
            double upperMiantong = meanOrdinateL2 - meanOrdinateL1;
            double upperJicaitong = meanOrdinateL3 - meanOrdinateL2;
            double upperMian_Jicaitong = meanOrdinateL3 - meanOrdinateL1;
            double lowerMiantong = meanOrdinateL6 - meanOrdinateL5;
            double lowerJicaitong = meanOrdinateL5 - meanOrdinateL4;
            double lowerMian_Jicaitong = meanOrdinateL6 - meanOrdinateL4;
            double kongtong = abscissaV1 - abscissaV2;

            // 八、标记
            int middle = (dataArea[0] + dataArea[1]) / 2;
            int middle2 = (int)((meanOrdinateL3 + meanOrdinateL4) / 2);
            // 上面铜
            SubFunction.LabelVertical(image, middle + 40, (int)meanOrdinateL1, middle + 40, (int)meanOrdinateL2, upperMiantong);
            // 上基材铜
            SubFunction.LabelVertical(image, middle - 40, (int)meanOrdinateL2, middle - 40, (int)meanOrdinateL3, upperJicaitong);
            // 上面铜+基材铜
            SubFunction.LabelVertical(image, middle, (int)meanOrdinateL1, middle, (int)meanOrdinateL3, upperMian_Jicaitong);
            // 下面铜
            SubFunction.LabelVertical(image, middle + 40, (int)meanOrdinateL5, middle + 40, (int)meanOrdinateL6, lowerMiantong);
            // 下基材铜
            SubFunction.LabelVertical(image, middle - 40, (int)meanOrdinateL4, middle - 40, (int)meanOrdinateL5, lowerJicaitong);
            // 下面铜+基材铜
            SubFunction.LabelVertical(image, middle, (int)meanOrdinateL4, middle, (int)meanOrdinateL6, lowerMian_Jicaitong);
            // 孔铜
            SubFunction.LableHorizontal(image, (int)abscissaV2, middle2, (int)abscissaV1, middle2, kongtong);
        }
        public static void CaokongSancengYou(string fileName)
        {
            // 一、预处理
            // 读取图片
            Mat image = new Mat(fileName, ImreadModes.Color);

            //获取图片的长宽
            int rows = image.Rows;
            int cols = image.Cols;

            // 转换为灰度图
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);

            //获得蓝色，绿色，红色通道图片
            Mat imageBlue, imageGreen, imageRed = new Mat(imageGray.Size(), imageGray.Type());
            SubFunction.SeparateRGB(image, out imageBlue, out imageGreen, out imageRed);

            // 二值化，获得目标区域
            Mat imageContour = imageGray.Threshold(0, 255, ThresholdTypes.Otsu);
            // 闭运算，消除小孔
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));// 结构元素
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Close, se);

            // 转成数组
            int[,] arrayContour = BasFunction.Mat2Array(imageContour);
            arrayContour = BasFunction.ConversionRange(arrayContour);

            // 去亮光
            int b2, b3;
            SubFunction.SplitArea(arrayContour, out b2, out b3);
            if ((b3 - b2) > 100)
            {
                Mat result = new Mat();
                BasFunction.SetNumber(imageContour, out result, 0, rows, 0, b3, 0);// 亮光区域置0
                imageContour = result;
            }

            // 边缘检测
            Mat imageOutlint = new Mat();
            SubFunction.Sobel(imageContour, out imageOutlint);

            int[,] arrayOutline = BasFunction.Mat2Array(imageOutlint);
            arrayOutline = BasFunction.ConversionRange(arrayOutline);

            // 二、计算数据提取区域
            // 对图片进行填充 
            Mat imageFill = new Mat();
            SubFunction.Fill(imageContour, out imageFill);

            // 计算数据提取区域
            int[] dataArea = new int[2];
            SubFunction.DataArea2(imageFill, out dataArea);

            // 三、提取L1，L3，L4，L5, L6, L8
            double meanOrdinateL1 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL1, dataArea[0], dataArea[1]);
            double meanOrdinateL3 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL3, dataArea[0], dataArea[1], meanOrdinateL1);
            double meanOrdinateL4 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL4, dataArea[0], dataArea[1], meanOrdinateL3);
            double meanOrdinateL5 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL5, dataArea[0], dataArea[1], meanOrdinateL4);
            double meanOrdinateL6 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL6, dataArea[0], dataArea[1], meanOrdinateL5);
            double meanOrdinateL8 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL8, dataArea[0], dataArea[1], meanOrdinateL6);

            // 四、提取L2
            double meanOrdinateL2 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateL1 + 10, (int)meanOrdinateL3 - 10, dataArea[0], dataArea[1], out meanOrdinateL2);

            // 五、提取L7
            double meanOrdinateL7 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateL6 + 10, (int)meanOrdinateL8 - 10, dataArea[0], dataArea[1], out meanOrdinateL7);

            // 六、提取胶体线
            Mat imageGlue = new Mat();
            SubFunction.GlueArea(imageContour, imageRed, out imageGlue, (int)meanOrdinateL5 + 10, (int)meanOrdinateL6 - 10, dataArea[0], dataArea[1]);

            // 转数组
            int[,] arrayGlue = BasFunction.Mat2Array(imageGlue);
            arrayGlue = BasFunction.ConversionRange(arrayGlue);

            // 提取胶体线
            double meanOrdinateLG = 0;
            SubFunction.InsideLine(imageGlue, (int)meanOrdinateL5 + 15, (int)meanOrdinateL6 - 15, dataArea[0], dataArea[1], out meanOrdinateLG);

            // 七、提取竖线V1、V2、V3、V4
            double abscissaV1 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline, out abscissaV1, (int)meanOrdinateL3, (int)meanOrdinateL4);
            double abscissaV2 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline, out abscissaV2, (int)meanOrdinateL3, (int)meanOrdinateL4, abscissaV1);
            double abscissaV3 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline, out abscissaV3, (int)meanOrdinateLG, (int)meanOrdinateL6);
            double abscissaV4 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline, out abscissaV4, (int)meanOrdinateLG, (int)meanOrdinateL6, abscissaV3);

            // 八、计算粗糙度
            int cucaodu;
            int[] cucaoduZuobiao = new int[2];
            SubFunction.Cucaodu(arrayOutline, (int)meanOrdinateL5 + 60, (int)meanOrdinateL6 - 30, (int)abscissaV4, out cucaodu, out cucaoduZuobiao);

            // 九、计算数据
            double upperMiantong = meanOrdinateL2 - meanOrdinateL1;
            double upperJicaitong = meanOrdinateL3 - meanOrdinateL2;
            double upperMian_Jicaitong = meanOrdinateL3 - meanOrdinateL1;
            double lowerMiantong = meanOrdinateL8 - meanOrdinateL7;
            double lowerJicaitong = meanOrdinateL7 - meanOrdinateL6;
            double lowerMian_Jicaitong = meanOrdinateL8 - meanOrdinateL6;
            double upperKongtong = abscissaV2 - abscissaV1;
            double lowerKongtong = abscissaV4 - abscissaV3;

            // 十、标记
            int middle = (dataArea[0] + dataArea[1]) / 2;
            int middle2 = (int)(meanOrdinateL3 + meanOrdinateL4) / 2;
            int middle3 = (int)(meanOrdinateLG + meanOrdinateL6) / 2;
            // 上面铜
            SubFunction.LabelVertical(image, middle - 40, (int)meanOrdinateL1, middle - 40, (int)meanOrdinateL2, upperMiantong);
            // 上基材铜
            SubFunction.LabelVertical(image, middle + 40, (int)meanOrdinateL2, middle + 40, (int)meanOrdinateL3, upperJicaitong);
            // 上面铜+基材铜
            SubFunction.LabelVertical(image, middle, (int)meanOrdinateL1, middle, (int)meanOrdinateL3, upperMian_Jicaitong);
            // 下面铜
            SubFunction.LabelVertical(image, middle - 40, (int)meanOrdinateL8, middle - 40, (int)meanOrdinateL7, lowerMiantong);
            // 下基材铜
            SubFunction.LabelVertical(image, middle + 40, (int)meanOrdinateL7, middle + 40, (int)meanOrdinateL6, lowerJicaitong);
            // 下面铜+基材铜
            SubFunction.LabelVertical(image, middle, (int)meanOrdinateL8, middle, (int)meanOrdinateL6, lowerMian_Jicaitong);
            // 上孔铜
            SubFunction.LableHorizontal(image, (int)abscissaV1, middle2, (int)abscissaV2, middle2, upperKongtong);
            // 下孔铜
            SubFunction.LableHorizontal(image, (int)abscissaV3, middle3, (int)abscissaV4, middle3, lowerKongtong);
            // 粗糙度
            SubFunction.LableHorizontal(image, (int)abscissaV4, cucaoduZuobiao[0], cucaoduZuobiao[1], cucaoduZuobiao[0], cucaodu);
        }
        public static void CaokongSancengZuo(string fileName)
        {
            // 一、预处理
            // 读取图片
            Mat image = new Mat(fileName, ImreadModes.Color);

            //获取图片的长宽
            int rows = image.Rows;
            int cols = image.Cols;

            // 转换为灰度图
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);

            //获得蓝色，绿色，红色通道图片
            Mat imageBlue, imageGreen, imageRed = new Mat(imageGray.Size(), imageGray.Type());
            SubFunction.SeparateRGB(image, out imageBlue, out imageGreen, out imageRed);

            // 二值化，获得目标区域
            Mat imageContour = imageGray.Threshold(0, 255, ThresholdTypes.Otsu);
            // 闭运算，消除小孔
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));// 结构元素
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Close, se);

            // 转成数组
            int[,] arrayContour = BasFunction.Mat2Array(imageContour);
            arrayContour = BasFunction.ConversionRange(arrayContour);

            // 去亮光
            int b2, b3;
            SubFunction.SplitArea(arrayContour, out b2, out b3);
            if ((b3 - b2) > 100)
            {
                Mat result = new Mat();
                BasFunction.SetNumber(imageContour, out result, 0, rows, b2, cols, 0);// 亮光区域置0
                imageContour = result;
            }

            // 边缘检测
            Mat imageOutlint = new Mat();
            SubFunction.Sobel(imageContour, out imageOutlint);

            int[,] arrayOutline = BasFunction.Mat2Array(imageOutlint);
            arrayOutline = BasFunction.ConversionRange(arrayOutline);

            // 二、计算数据提取区域
            // 对图片进行填充 
            Mat imageFill = new Mat();
            SubFunction.Fill(imageContour, out imageFill);

            // 计算数据提取区域
            int[] dataArea = new int[2];
            SubFunction.DataArea2(imageFill, out dataArea);

            // 三、提取L1，L3，L4，L5, L6, L8
            double meanOrdinateL1 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL1, dataArea[0], dataArea[1]);
            double meanOrdinateL3 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL3, dataArea[0], dataArea[1], meanOrdinateL1);
            double meanOrdinateL4 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL4, dataArea[0], dataArea[1], meanOrdinateL3);
            double meanOrdinateL5 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL5, dataArea[0], dataArea[1], meanOrdinateL4);
            double meanOrdinateL6 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL6, dataArea[0], dataArea[1], meanOrdinateL5);
            double meanOrdinateL8 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL6, dataArea[0], dataArea[1], meanOrdinateL8);

            // 四、提取L2
            double meanOrdinateL2 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateL1 + 10, (int)meanOrdinateL3 - 10, dataArea[0], dataArea[1], out meanOrdinateL2);

            // 五、提取L7
            double meanOrdinateL7 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateL6 + 10, (int)meanOrdinateL8 - 10, dataArea[0], dataArea[1], out meanOrdinateL7);

            // 六、提取胶体线
            Mat imageGlue = new Mat();
            SubFunction.GlueArea(imageContour, imageRed, out imageGlue, (int)meanOrdinateL5 + 10, (int)meanOrdinateL6 - 10, dataArea[0], dataArea[1]);

            // 转数组
            int[,] arrayGlue = BasFunction.Mat2Array(imageGlue);
            arrayGlue = BasFunction.ConversionRange(arrayGlue);

            // 提取胶体线
            double meanOrdinateLG = 0;
            SubFunction.InsideLine(imageGlue, (int)meanOrdinateL5 + 15, (int)meanOrdinateL6 - 15, dataArea[0], dataArea[1], out meanOrdinateLG);

            // 七、提取竖线V1、V2、V3、V4
            double abscissaV1 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline, out abscissaV1, (int)meanOrdinateL3, (int)meanOrdinateL4);
            double abscissaV2 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline, out abscissaV2, (int)meanOrdinateL3, (int)meanOrdinateL4, abscissaV1);
            double abscissaV3 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline, out abscissaV3, (int)meanOrdinateLG, (int)meanOrdinateL6);
            double abscissaV4 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline, out abscissaV4, (int)meanOrdinateLG, (int)meanOrdinateL6, abscissaV3);

            // 八、计算粗糙度
            int cucaodu;
            int[] cucaoduZuobiao = new int[2];
            SubFunction.Cucaodu(arrayOutline, (int)meanOrdinateL5 + 60, (int)meanOrdinateL6 - 30, (int)abscissaV4, out cucaodu, out cucaoduZuobiao);

            // 九、计算数据
            double upperMiantong = meanOrdinateL2 - meanOrdinateL1;
            double upperJicaitong = meanOrdinateL3 - meanOrdinateL2;
            double upperMian_Jicaitong = meanOrdinateL3 - meanOrdinateL1;
            double lowerMiantong = meanOrdinateL8 - meanOrdinateL7;
            double lowerJicaitong = meanOrdinateL7 - meanOrdinateL6;
            double lowerMian_Jicaitong = meanOrdinateL8 - meanOrdinateL6;
            double upperKongtong = abscissaV1 - abscissaV2;
            double lowerKongtong = abscissaV3 - abscissaV4;

            // 十、标记
            int middle = (dataArea[0] + dataArea[1]) / 2;
            int middle2 = (int)(meanOrdinateL3 + meanOrdinateL4) / 2;
            int middle3 = (int)(meanOrdinateLG + meanOrdinateL6) / 2;
            // 上面铜
            SubFunction.LabelVertical(image, middle - 40, (int)meanOrdinateL1, middle - 40, (int)meanOrdinateL2, upperMiantong);
            // 上基材铜
            SubFunction.LabelVertical(image, middle + 40, (int)meanOrdinateL2, middle + 40, (int)meanOrdinateL3, upperJicaitong);
            // 上面铜+基材铜
            SubFunction.LabelVertical(image, middle, (int)meanOrdinateL1, middle, (int)meanOrdinateL3, upperMian_Jicaitong);
            // 下面铜
            SubFunction.LabelVertical(image, middle - 40, (int)meanOrdinateL8, middle - 40, (int)meanOrdinateL7, lowerMiantong);
            // 下基材铜
            SubFunction.LabelVertical(image, middle + 40, (int)meanOrdinateL7, middle + 40, (int)meanOrdinateL6, lowerJicaitong);
            // 下面铜+基材铜
            SubFunction.LabelVertical(image, middle, (int)meanOrdinateL8, middle, (int)meanOrdinateL6, lowerMian_Jicaitong);
            // 上孔铜
            SubFunction.LableHorizontal(image, (int)abscissaV1, middle2, (int)abscissaV2, middle2, upperKongtong);
            // 下孔铜
            SubFunction.LableHorizontal(image, (int)abscissaV3, middle3, (int)abscissaV4, middle3, lowerKongtong);
            // 粗糙度
            SubFunction.LableHorizontal(image, (int)abscissaV4, cucaoduZuobiao[0], cucaoduZuobiao[1], cucaoduZuobiao[0], cucaodu);

        }       
        public static void CaokongSicengYou(string fileName)
        {
            // 一、预处理
            // 读取图片
            Mat image = new Mat(fileName, ImreadModes.Color);

            //获取图片的长宽
            int rows = image.Rows;
            int cols = image.Cols;

            // 转换为灰度图
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);

            //获得蓝色，绿色，红色通道图片
            Mat imageBlue, imageGreen, imageRed = new Mat(imageGray.Size(), imageGray.Type());
            SubFunction.SeparateRGB(image, out imageBlue, out imageGreen, out imageRed);

            // 二值化，获得目标区域
            Mat imageContour = imageGray.Threshold(0, 255, ThresholdTypes.Otsu);
            // 闭运算，消除小孔
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));// 结构元素
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Close, se);

            // 去亮光
            Mat result = new Mat();
            SubFunction.RemoveLightSiceng(imageContour, imageRed, out result, "right");
            imageContour = result;

            // 转成数组
            int[,] arrayContour = BasFunction.Mat2Array(imageContour);
            arrayContour = BasFunction.ConversionRange(arrayContour);

            // 边缘检测
            Mat imageOutlint = new Mat();
            SubFunction.Sobel(imageContour, out imageOutlint);

            int[,] arrayOutline = BasFunction.Mat2Array(imageOutlint);
            arrayOutline = BasFunction.ConversionRange(arrayOutline);

            // 二、计算数据提取区域
            // 对图片进行填充 
            Mat imageFill = new Mat();
            SubFunction.Fill(imageContour, out imageFill);

            // 计算数据提取区域
            int[] dataArea = new int[2];
            SubFunction.DataArea2(imageFill, out dataArea);

            // 三、提取L1，L3，L4，L5, L6, L7, L8, L10
            double meanOrdinateL1 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL1, dataArea[0], dataArea[1]);
            double meanOrdinateL3 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL3, dataArea[0], dataArea[1], meanOrdinateL1);
            double meanOrdinateL4 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL4, dataArea[0], dataArea[1], meanOrdinateL3);
            double meanOrdinateL5 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL5, dataArea[0], dataArea[1], meanOrdinateL4);
            double meanOrdinateL6 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL6, dataArea[0], dataArea[1], meanOrdinateL5);
            double meanOrdinateL7 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL7, dataArea[0], dataArea[1], meanOrdinateL6);
            double meanOrdinateL8 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL8, dataArea[0], dataArea[1], meanOrdinateL7);
            double meanOrdinateL10 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL10, dataArea[0], dataArea[1], meanOrdinateL8);

            // 四、提取L2
            double meanOrdinateL2 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateL1 + 10, (int)meanOrdinateL3 - 10, dataArea[0], dataArea[1], out meanOrdinateL2);

            // 五、提取L7
            double meanOrdinateL9 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateL8 + 10, (int)meanOrdinateL10 - 10, dataArea[0], dataArea[1], out meanOrdinateL10);

            // 六、提取胶体线
            Mat imageGlue1 = new Mat();
            SubFunction.GlueArea(imageContour, imageRed, out imageGlue1, (int)meanOrdinateL3 + 10, (int)meanOrdinateL4 - 10, dataArea[0], dataArea[1]);
            Mat imageGlue2 = new Mat();
            SubFunction.GlueArea(imageContour, imageRed, out imageGlue2, (int)meanOrdinateL7 + 10, (int)meanOrdinateL8 - 10, dataArea[0], dataArea[1]);

            // 转数组
            int[,] arrayGlue1 = BasFunction.Mat2Array(imageGlue1);
            arrayGlue1 = BasFunction.ConversionRange(arrayGlue1);
            int[,] arrayGlue2 = BasFunction.Mat2Array(imageGlue2);
            arrayGlue2 = BasFunction.ConversionRange(arrayGlue2);

            // 提取胶体线
            double meanOrdinateLG1 = 0;
            SubFunction.InsideLine(imageGlue1, (int)meanOrdinateL3 + 15, (int)meanOrdinateL4 - 15, dataArea[0], dataArea[1], out meanOrdinateLG1);
            double meanOrdinateLG2 = 0;
            SubFunction.InsideLine(imageGlue1, (int)meanOrdinateL7 + 15, (int)meanOrdinateL8 - 15, dataArea[0], dataArea[1], out meanOrdinateLG2);

            // 七、提取竖线V1、V2、V3、V4、V5、V6
            double abscissaV1 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline, out abscissaV1, (int)meanOrdinateL3, (int)meanOrdinateLG1);
            double abscissaV2 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline, out abscissaV2, (int)meanOrdinateL3, (int)meanOrdinateLG1, abscissaV1);
            double abscissaV3 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline, out abscissaV3, (int)meanOrdinateL5, (int)meanOrdinateL6);
            double abscissaV4 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline, out abscissaV4, (int)meanOrdinateL5, (int)meanOrdinateL6, abscissaV3);
            double abscissaV5 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline, out abscissaV5, (int)meanOrdinateLG2, (int)meanOrdinateL8);
            double abscissaV6 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline, out abscissaV6, (int)meanOrdinateLG2, (int)meanOrdinateL8, abscissaV5);

            // 八、计算粗糙度
            int cucaodu1;
            int[] cucaoduZuobiao1 = new int[2];
            SubFunction.Cucaodu(arrayOutline, (int)meanOrdinateL3 + 60, (int)meanOrdinateL4 - 30, (int)abscissaV2, out cucaodu1, out cucaoduZuobiao1);
            int cucaodu2;
            int[] cucaoduZuobiao2 = new int[2];
            SubFunction.Cucaodu(arrayOutline, (int)meanOrdinateL7 + 60, (int)meanOrdinateL8 - 30, (int)abscissaV6, out cucaodu2, out cucaoduZuobiao2);

            // 九、计算数据
            double upperMiantong = meanOrdinateL2 - meanOrdinateL1;
            double upperJicaitong = meanOrdinateL3 - meanOrdinateL2;
            double upperMian_Jicaitong = meanOrdinateL3 - meanOrdinateL1;
            double lowerMiantong = meanOrdinateL10 - meanOrdinateL8;
            double lowerJicaitong = meanOrdinateL9 - meanOrdinateL8;
            double lowerMian_Jicaitong = meanOrdinateL10 - meanOrdinateL8;
            double upperKongtong = abscissaV2 - abscissaV1;
            double middleKongtong = abscissaV4 - abscissaV3;
            double lowerKongtong = abscissaV6 - abscissaV5;

            // 十、标记
            int middle = (dataArea[0] + dataArea[1]) / 2;// 面铜+基材铜横坐标
            int middle2 = (int)(meanOrdinateL3 + meanOrdinateLG1) / 2;// 孔铜1纵坐标
            int middle3 = (int)(meanOrdinateL5 + meanOrdinateL6) / 2;// 孔铜2纵坐标
            int middle4 = (int)(meanOrdinateLG2 + meanOrdinateL8) / 2;// 孔铜3纵坐标
            // 上面铜
            SubFunction.LabelVertical(image, middle - 40, (int)meanOrdinateL1, middle - 40, (int)meanOrdinateL2, upperMiantong);
            // 上基材铜
            SubFunction.LabelVertical(image, middle + 40, (int)meanOrdinateL2, middle + 40, (int)meanOrdinateL3, upperJicaitong);
            // 上面铜+基材铜
            SubFunction.LabelVertical(image, middle, (int)meanOrdinateL1, middle, (int)meanOrdinateL3, upperMian_Jicaitong);
            // 下面铜
            SubFunction.LabelVertical(image, middle - 40, (int)meanOrdinateL8, middle - 40, (int)meanOrdinateL7, lowerMiantong);
            // 下基材铜
            SubFunction.LabelVertical(image, middle + 40, (int)meanOrdinateL7, middle + 40, (int)meanOrdinateL6, lowerJicaitong);
            // 下面铜+基材铜
            SubFunction.LabelVertical(image, middle, (int)meanOrdinateL8, middle, (int)meanOrdinateL6, lowerMian_Jicaitong);
            // 上孔铜
            SubFunction.LableHorizontal(image, (int)abscissaV1, middle2, (int)abscissaV2, middle2, upperKongtong);
            // 中孔铜
            SubFunction.LableHorizontal(image, (int)abscissaV3, middle3, (int)abscissaV4, middle3, middleKongtong);
            // 下孔铜
            SubFunction.LableHorizontal(image, (int)abscissaV5, middle4, (int)abscissaV6, middle4, lowerKongtong);
            // 粗糙度1
            SubFunction.LableHorizontal(image, (int)abscissaV2, cucaoduZuobiao1[0], cucaoduZuobiao1[1], cucaoduZuobiao1[0], cucaodu1);
            // 粗糙度2
            SubFunction.LableHorizontal(image, (int)abscissaV6, cucaoduZuobiao2[0], cucaoduZuobiao2[1], cucaoduZuobiao2[0], cucaodu2);
        }
        public static void CaokongSicengZuo(string fileName)
        {
            // 一、预处理
            // 读取图片
            Mat image = new Mat(fileName, ImreadModes.Color);

            //获取图片的长宽
            int rows = image.Rows;
            int cols = image.Cols;

            // 转换为灰度图
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);

            //获得蓝色，绿色，红色通道图片
            Mat imageBlue, imageGreen, imageRed = new Mat(imageGray.Size(), imageGray.Type());
            SubFunction.SeparateRGB(image, out imageBlue, out imageGreen, out imageRed);

            // 二值化，获得目标区域
            Mat imageContour = imageGray.Threshold(0, 255, ThresholdTypes.Otsu);
            // 闭运算，消除小孔
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));// 结构元素
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Close, se);

            // 去亮光
            Mat result = new Mat();
            SubFunction.RemoveLightSiceng(imageContour, imageRed, out result, "left");
            imageContour = result;

            // 转成数组
            int[,] arrayContour = BasFunction.Mat2Array(imageContour);
            arrayContour = BasFunction.ConversionRange(arrayContour);

            // 边缘检测
            Mat imageOutlint = new Mat();
            SubFunction.Sobel(imageContour, out imageOutlint);

            int[,] arrayOutline = BasFunction.Mat2Array(imageOutlint);
            arrayOutline = BasFunction.ConversionRange(arrayOutline);

            // 二、计算数据提取区域
            // 对图片进行填充 
            Mat imageFill = new Mat();
            SubFunction.Fill(imageContour, out imageFill);

            // 计算数据提取区域
            int[] dataArea = new int[2];
            SubFunction.DataArea2(imageFill, out dataArea);

            // 三、提取L1，L3，L4，L5, L6, L7, L8, L10
            double meanOrdinateL1 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL1, dataArea[0], dataArea[1]);
            double meanOrdinateL3 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL3, dataArea[0], dataArea[1], meanOrdinateL1);
            double meanOrdinateL4 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL4, dataArea[0], dataArea[1], meanOrdinateL3);
            double meanOrdinateL5 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL5, dataArea[0], dataArea[1], meanOrdinateL4);
            double meanOrdinateL6 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL6, dataArea[0], dataArea[1], meanOrdinateL5);
            double meanOrdinateL7 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL7, dataArea[0], dataArea[1], meanOrdinateL6);
            double meanOrdinateL8 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL8, dataArea[0], dataArea[1], meanOrdinateL7);
            double meanOrdinateL10 = 0;
            SubFunction.ExtractLines(arrayOutline, out meanOrdinateL10, dataArea[0], dataArea[1], meanOrdinateL8);

            // 四、提取L2
            double meanOrdinateL2 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateL1 + 10, (int)meanOrdinateL3 - 10, dataArea[0], dataArea[1], out meanOrdinateL2);

            // 五、提取L7
            double meanOrdinateL9 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateL8 + 10, (int)meanOrdinateL10 - 10, dataArea[0], dataArea[1], out meanOrdinateL10);

            // 六、提取胶体线
            Mat imageGlue1 = new Mat();
            SubFunction.GlueArea(imageContour, imageRed, out imageGlue1, (int)meanOrdinateL3 + 10, (int)meanOrdinateL4 - 10, dataArea[0], dataArea[1]);
            Mat imageGlue2 = new Mat();
            SubFunction.GlueArea(imageContour, imageRed, out imageGlue2, (int)meanOrdinateL7 + 10, (int)meanOrdinateL8 - 10, dataArea[0], dataArea[1]);

            // 转数组
            int[,] arrayGlue1 = BasFunction.Mat2Array(imageGlue1);
            arrayGlue1 = BasFunction.ConversionRange(arrayGlue1);
            int[,] arrayGlue2 = BasFunction.Mat2Array(imageGlue2);
            arrayGlue2 = BasFunction.ConversionRange(arrayGlue2);

            // 提取胶体线
            double meanOrdinateLG1 = 0;
            SubFunction.InsideLine(imageGlue1, (int)meanOrdinateL3 + 15, (int)meanOrdinateL4 - 15, dataArea[0], dataArea[1], out meanOrdinateLG1);
            double meanOrdinateLG2 = 0;
            SubFunction.InsideLine(imageGlue1, (int)meanOrdinateL7 + 15, (int)meanOrdinateL8 - 15, dataArea[0], dataArea[1], out meanOrdinateLG2);

            // 七、提取竖线V1、V2、V3、V4、V5、V6
            double abscissaV1 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline, out abscissaV1, (int)meanOrdinateL3, (int)meanOrdinateLG1);
            double abscissaV2 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline, out abscissaV2, (int)meanOrdinateL3, (int)meanOrdinateLG1, abscissaV1);
            double abscissaV3 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline, out abscissaV3, (int)meanOrdinateL5, (int)meanOrdinateL6);
            double abscissaV4 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline, out abscissaV4, (int)meanOrdinateL5, (int)meanOrdinateL6, abscissaV3);
            double abscissaV5 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline, out abscissaV5, (int)meanOrdinateLG2, (int)meanOrdinateL8);
            double abscissaV6 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline, out abscissaV6, (int)meanOrdinateLG2, (int)meanOrdinateL8, abscissaV5);

            // 八、计算粗糙度
            int cucaodu1;
            int[] cucaoduZuobiao1 = new int[2];
            SubFunction.Cucaodu(arrayOutline, (int)meanOrdinateL3 + 60, (int)meanOrdinateL4 - 30, (int)abscissaV2, out cucaodu1, out cucaoduZuobiao1);
            int cucaodu2;
            int[] cucaoduZuobiao2 = new int[2];
            SubFunction.Cucaodu(arrayOutline, (int)meanOrdinateL7 + 60, (int)meanOrdinateL8 - 30, (int)abscissaV6, out cucaodu2, out cucaoduZuobiao2);

            // 九、计算数据
            double upperMiantong = meanOrdinateL2 - meanOrdinateL1;
            double upperJicaitong = meanOrdinateL3 - meanOrdinateL2;
            double upperMian_Jicaitong = meanOrdinateL3 - meanOrdinateL1;
            double lowerMiantong = meanOrdinateL10 - meanOrdinateL8;
            double lowerJicaitong = meanOrdinateL9 - meanOrdinateL8;
            double lowerMian_Jicaitong = meanOrdinateL10 - meanOrdinateL8;
            double upperKongtong = abscissaV1 - abscissaV2;
            double middleKongtong = abscissaV3 - abscissaV4;
            double lowerKongtong = abscissaV5 - abscissaV6;

            // 十、标记
            int middle = (dataArea[0] + dataArea[1]) / 2;// 面铜+基材铜横坐标
            int middle2 = (int)(meanOrdinateL3 + meanOrdinateLG1) / 2;// 孔铜1纵坐标
            int middle3 = (int)(meanOrdinateL5 + meanOrdinateL6) / 2;// 孔铜2纵坐标
            int middle4 = (int)(meanOrdinateLG2 + meanOrdinateL8) / 2;// 孔铜3纵坐标
            // 上面铜
            SubFunction.LabelVertical(image, middle - 40, (int)meanOrdinateL1, middle - 40, (int)meanOrdinateL2, upperMiantong);
            // 上基材铜
            SubFunction.LabelVertical(image, middle + 40, (int)meanOrdinateL2, middle + 40, (int)meanOrdinateL3, upperJicaitong);
            // 上面铜+基材铜
            SubFunction.LabelVertical(image, middle, (int)meanOrdinateL1, middle, (int)meanOrdinateL3, upperMian_Jicaitong);
            // 下面铜
            SubFunction.LabelVertical(image, middle - 40, (int)meanOrdinateL8, middle - 40, (int)meanOrdinateL7, lowerMiantong);
            // 下基材铜
            SubFunction.LabelVertical(image, middle + 40, (int)meanOrdinateL7, middle + 40, (int)meanOrdinateL6, lowerJicaitong);
            // 下面铜+基材铜
            SubFunction.LabelVertical(image, middle, (int)meanOrdinateL8, middle, (int)meanOrdinateL6, lowerMian_Jicaitong);
            // 上孔铜
            SubFunction.LableHorizontal(image, (int)abscissaV1, middle2, (int)abscissaV2, middle2, upperKongtong);
            // 中孔铜
            SubFunction.LableHorizontal(image, (int)abscissaV3, middle3, (int)abscissaV4, middle3, middleKongtong);
            // 下孔铜
            SubFunction.LableHorizontal(image, (int)abscissaV5, middle4, (int)abscissaV6, middle4, lowerKongtong);
            // 粗糙度1
            SubFunction.LableHorizontal(image, (int)abscissaV2, cucaoduZuobiao1[0], cucaoduZuobiao1[1], cucaoduZuobiao1[0], cucaodu1);
            // 粗糙度2
            SubFunction.LableHorizontal(image, (int)abscissaV6, cucaoduZuobiao2[0], cucaoduZuobiao2[1], cucaoduZuobiao2[0], cucaodu2);
        }
        public static void CaokongSicengZhong(string fileName)
        {
            // 一、预处理
            // 读取图片
            Mat image = new Mat(fileName, ImreadModes.Color);

            //获取图片的长宽
            int rows = image.Rows;
            int cols = image.Cols;

            // 转换为灰度图
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);

            //获得蓝色，绿色，红色通道图片
            Mat imageBlue, imageGreen, imageRed = new Mat(imageGray.Size(), imageGray.Type());
            SubFunction.SeparateRGB(image, out imageBlue, out imageGreen, out imageRed);

            // 重新修改比例调色
            Mat imageNew = new Mat(imageRed.Size(), imageRed.Type());
            imageNew = 0.9 * imageGreen + 0.1 * imageRed;

            // 均值滤波
            Mat imageFilter = new Mat();
            Cv2.Blur(imageNew, imageFilter, new Size(5, 5));

            // 二值化，获得目标区域
            Mat imageContourText = imageFilter.Threshold(0, 255, ThresholdTypes.Otsu);// 用来计算消除亮光的边界
            Mat imageContour = imageRed.Threshold(0, 255, ThresholdTypes.Otsu);

            // 转成数组
            int[,] arrayContourText = BasFunction.Mat2Array(imageContourText);
            arrayContourText = BasFunction.ConversionRange(arrayContourText);

            // 将中间亮光置0
            int b2, b3;
            SubFunction.SplitArea(arrayContourText, out b2, out b3);
            Mat result = new Mat();
            BasFunction.SetNumber(imageContour, out result, 0, rows, b2, b3, 0);// 亮光区域置0
            imageContour = result;

            // 闭运算，消除小孔
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));// 结构元素
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Close, se);

            // 将原图分为两部分
            int dividingLine = (b2 + b3) / 2;
            Mat imageContour1 = imageContour;
            Mat imageContour2 = imageContour;
            for (int i = 0; i < rows; i++)
            {
                for (int j = 0; j < dividingLine; j++)
                {
                    imageContour2.Set<int>(i, j, 0);
                }
                for (int k = dividingLine; k < cols; k++)
                {
                    imageContour1.Set<int>(i, k, 0);
                }
            }

            // 边缘检测
            Mat imageOutline1;
            Mat imageOutline2;
            SubFunction.Sobel(imageContour1, out imageOutline1);
            SubFunction.Sobel(imageContour2, out imageOutline2);

            // 转成数组
            int[,] arrayOutline1 = BasFunction.Mat2Array(imageOutline1);
            arrayOutline1 = BasFunction.ConversionRange(arrayOutline1);
            int[,] arrayOutline2 = BasFunction.Mat2Array(imageOutline2);
            arrayOutline2 = BasFunction.ConversionRange(arrayOutline2);

            // 计算图像1（左）
            // 二、计算数据提取区域
            // 对图片进行填充 
            Mat imageFill = new Mat();
            SubFunction.Fill(imageContour1, out imageFill);

            // 计算数据提取区域
            int[] dataArea = new int[2];
            SubFunction.DataArea2(imageFill, out dataArea);

            // 三、提取L1，L3，L4，L5, L6, L7, L8, L10 
            double meanOrdinateLeft1 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft1, dataArea[0], dataArea[1]);
            double meanOrdinateLeft3 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft3, dataArea[0], dataArea[1], meanOrdinateLeft1);
            double meanOrdinateLeft4 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft4, dataArea[0], dataArea[1], meanOrdinateLeft3);
            double meanOrdinateLeft5 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft5, dataArea[0], dataArea[1], meanOrdinateLeft4);
            double meanOrdinateLeft6 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft6, dataArea[0], dataArea[1], meanOrdinateLeft5);
            double meanOrdinateLeft7 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft7, dataArea[0], dataArea[1], meanOrdinateLeft6);
            double meanOrdinateLeft8 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft8, dataArea[0], dataArea[1], meanOrdinateLeft7);
            double meanOrdinateLeft10 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft10, dataArea[0], dataArea[1], meanOrdinateLeft8);

            // 四、提取L2
            double meanOrdinateLeft2 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateLeft1 + 10, (int)meanOrdinateLeft3 - 10, dataArea[0], dataArea[1], out meanOrdinateLeft2);

            // 五、提取L7
            double meanOrdinateLeft9 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateLeft8 + 10, (int)meanOrdinateLeft10 - 10, dataArea[0], dataArea[1], out meanOrdinateLeft9);

            // 六、提取胶体线
            Mat imageGlueLeft1 = new Mat();
            SubFunction.GlueArea(imageContour1, imageRed, out imageGlueLeft1, (int)meanOrdinateLeft3 + 10, (int)meanOrdinateLeft4 - 10, dataArea[0], dataArea[1]);
            Mat imageGlueLeft2 = new Mat();
            SubFunction.GlueArea(imageContour1, imageRed, out imageGlueLeft2, (int)meanOrdinateLeft7 + 10, (int)meanOrdinateLeft8 - 10, dataArea[0], dataArea[1]);

            // 转数组
            int[,] arrayGlueLeft1 = BasFunction.Mat2Array(imageGlueLeft1);
            arrayGlueLeft1 = BasFunction.ConversionRange(arrayGlueLeft1);
            int[,] arrayGlueLeft2 = BasFunction.Mat2Array(imageGlueLeft2);
            arrayGlueLeft2 = BasFunction.ConversionRange(arrayGlueLeft2);

            // 提取胶体线
            double meanOrdinateLG1 = 0;
            SubFunction.InsideLine(imageGlueLeft1, (int)meanOrdinateLeft3 + 15, (int)meanOrdinateLeft4 - 15, dataArea[0], dataArea[1], out meanOrdinateLG1);
            double meanOrdinateLG2 = 0;
            SubFunction.InsideLine(imageGlueLeft2, (int)meanOrdinateLeft7 + 15, (int)meanOrdinateLeft8 - 15, dataArea[0], dataArea[1], out meanOrdinateLG2);

            // 七、提竖线V1,V2, V3, V4, V5, V6
            double abscissaVLeft1 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline1, out abscissaVLeft1, (int)meanOrdinateLeft3, (int)meanOrdinateLG1);
            double abscissaVLeft2 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline1, out abscissaVLeft2, (int)meanOrdinateLeft3, (int)meanOrdinateLG1, abscissaVLeft1);
            double abscissaVLeft3 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline1, out abscissaVLeft3, (int)meanOrdinateLeft5, (int)meanOrdinateLeft6);
            double abscissaVLeft4 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline1, out abscissaVLeft4, (int)meanOrdinateLeft5, (int)meanOrdinateLeft6, abscissaVLeft3);
            double abscissaVLeft5 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline1, out abscissaVLeft5, (int)meanOrdinateLG2, (int)meanOrdinateLeft8);
            double abscissaVLeft6 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline1, out abscissaVLeft6, (int)meanOrdinateLG2, (int)meanOrdinateLeft8, abscissaVLeft5);

            // 八、计算粗糙度
            int cucaoduLeft1 = 0;
            int[] cucaoduZuobiaoLeft1 = new int[2];
            SubFunction.Cucaodu(arrayOutline1, (int)meanOrdinateLeft3 + 60, (int)meanOrdinateLeft4 - 30, (int)abscissaVLeft2, out cucaoduLeft1, out cucaoduZuobiaoLeft1);
            int cucaoduLeft2 = 0;
            int[] cucaoduZuobiaoLeft2 = new int[2];
            SubFunction.Cucaodu(arrayOutline1, (int)meanOrdinateLeft7 + 60, (int)meanOrdinateLeft8 - 30, (int)abscissaVLeft6, out cucaoduLeft2, out cucaoduZuobiaoLeft2);

            // 计算图像2（右）
            // 二、计算数据提取区域
            // 对图片进行填充 
            Mat imageFill2 = new Mat();
            SubFunction.Fill(imageContour2, out imageFill);

            // 计算数据提取区域
            int[] dataArea2 = new int[2];
            SubFunction.DataArea2(imageFill2, out dataArea2);

            // 三、提取L1，L3，L4，L5, L6, L7, L8, L10
            double meanOrdinateRight1 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight1, dataArea2[0], dataArea2[1]);
            double meanOrdinateRight3 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight3, dataArea2[0], dataArea2[1], meanOrdinateRight1);
            double meanOrdinateRight4 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight4, dataArea2[0], dataArea2[1], meanOrdinateRight3);
            double meanOrdinateRight5 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight5, dataArea2[0], dataArea2[1], meanOrdinateRight4);
            double meanOrdinateRight6 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight6, dataArea2[0], dataArea2[1], meanOrdinateRight5);
            double meanOrdinateRight7 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight7, dataArea2[0], dataArea2[1], meanOrdinateRight6);
            double meanOrdinateRight8 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight8, dataArea2[0], dataArea2[1], meanOrdinateRight7);
            double meanOrdinateRight10 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight10, dataArea2[0], dataArea2[1], meanOrdinateRight8);

            // 四、提取L2
            double meanOrdinateRight2 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateRight1 + 10, (int)meanOrdinateRight3 - 10, dataArea2[0], dataArea2[1], out meanOrdinateRight2);

            // 五、提取L9
            double meanOrdinateRight9 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateRight8 + 10, (int)meanOrdinateRight10 - 10, dataArea2[0], dataArea2[1], out meanOrdinateRight9);

            // 六、提取胶体线
            Mat imageGlueRight1 = new Mat();
            SubFunction.GlueArea(imageContour2, imageRed, out imageGlueRight1, (int)meanOrdinateRight3 + 10, (int)meanOrdinateRight4 - 10, dataArea2[0], dataArea2[1]);
            Mat imageGlueRight2 = new Mat();
            SubFunction.GlueArea(imageContour2, imageRed, out imageGlueRight2, (int)meanOrdinateRight7 + 10, (int)meanOrdinateRight8 - 10, dataArea2[0], dataArea2[1]);

            // 转数组
            int[,] arrayGlueRight1 = BasFunction.Mat2Array(imageGlueRight1);
            arrayGlueRight1 = BasFunction.ConversionRange(arrayGlueRight1);
            int[,] arrayGlueRight2 = BasFunction.Mat2Array(imageGlueRight2);
            arrayGlueRight2 = BasFunction.ConversionRange(arrayGlueRight2);

            // 提取胶体线
            double meanOrdinateRG1 = 0;
            SubFunction.InsideLine(imageGlueRight1, (int)meanOrdinateRight3 + 15, (int)meanOrdinateRight4 - 15, dataArea2[0], dataArea2[1], out meanOrdinateRG1);
            double meanOrdinateRG2 = 0;
            SubFunction.InsideLine(imageGlueRight2, (int)meanOrdinateRight7 + 15, (int)meanOrdinateRight8 - 15, dataArea2[0], dataArea2[1], out meanOrdinateRG2);

            // 七 、提竖线V1,V2, V3, V4, V5, V6
            double abscissaVRight1 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline2, out abscissaVRight1, (int)meanOrdinateRight3, (int)meanOrdinateRG1);
            double abscissaVRight2 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline2, out abscissaVRight2, (int)meanOrdinateRight3, (int)meanOrdinateRG1, abscissaVRight1);
            double abscissaVRight3 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline2, out abscissaVRight3, (int)meanOrdinateRight5, (int)meanOrdinateRight6);
            double abscissaVRight4 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline2, out abscissaVRight4, (int)meanOrdinateRight5, (int)meanOrdinateRight6, abscissaVRight3);
            double abscissaVRight5 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline2, out abscissaVRight5, (int)meanOrdinateRG2, (int)meanOrdinateRight8);
            double abscissaVRight6 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline2, out abscissaVRight6, (int)meanOrdinateRG2, (int)meanOrdinateRight8, abscissaVRight5);

            // 八、计算粗糙度
            int cucaoduRight1 = 0;
            int[] cucaoduZuobiaoRight1 = new int[2];
            SubFunction.Cucaodu(arrayOutline2, (int)meanOrdinateRight3 + 60, (int)meanOrdinateRight4 - 30, (int)abscissaVRight2, out cucaoduRight1, out cucaoduZuobiaoRight1);
            int cucaoduRight2 = 0;
            int[] cucaoduZuobiaoRight2 = new int[2];
            SubFunction.Cucaodu(arrayOutline2, (int)meanOrdinateRight7 + 60, (int)meanOrdinateRight8 - 30, (int)abscissaVRight6, out cucaoduRight2, out cucaoduZuobiaoRight2);


            // 九、数据计算
            // 左
            double leftUpperMiantong = meanOrdinateLeft2 - meanOrdinateLeft1;
            double leftUpperJicaitong = meanOrdinateLeft3 - meanOrdinateLeft2;
            double leftUpperMian_Jicaitong = meanOrdinateLeft3 - meanOrdinateLeft1;
            double leftLowerMiantong = meanOrdinateLeft10 - meanOrdinateLeft9;
            double leftLowerJicaitong = meanOrdinateLeft9 - meanOrdinateLeft8;
            double leftLowerMian_Jicaitong = meanOrdinateLeft10 - meanOrdinateLeft8;
            double leftKongtong1 = abscissaVLeft1 - abscissaVLeft2;
            double leftKongtong2 = abscissaVLeft3 - abscissaVLeft4;
            double leftKongtong3 = abscissaVLeft5 - abscissaVLeft6;
            // 右
            double rightUpperMiantong = meanOrdinateRight2 - meanOrdinateRight1;
            double rightUpperJicaitong = meanOrdinateRight3 - meanOrdinateRight2;
            double rightUpperMian_Jicaitong = meanOrdinateRight3 - meanOrdinateRight1;
            double rightLowerMiantong = meanOrdinateRight10 - meanOrdinateRight9;
            double rightLowerJicaitong = meanOrdinateRight9 - meanOrdinateRight8;
            double rightLowerMian_Jicaitong = meanOrdinateRight10 - meanOrdinateRight8;
            double rightKongtong1 = abscissaVRight2 - abscissaVRight1;
            double rightKongtong2 = abscissaVRight4 - abscissaVRight3;
            double rightKongtong3 = abscissaVRight6 - abscissaVRight5;

            double upperKongjing = abscissaVRight2 - abscissaVLeft2; ;
            double lowerKongjing = abscissaVRight6 - abscissaVLeft6;

            // 八、标记
            int middleLeft = (dataArea[0] + dataArea[1]) / 2;// 左边面铜+基材铜横坐标
            int middleLeft2 = (int)((meanOrdinateLeft3 + meanOrdinateLG1) / 2);// 左边孔铜1纵坐标
            int middleLeft3 = (int)((meanOrdinateLeft5 + meanOrdinateLeft6) / 2);// 左边孔铜2纵坐标
            int middleLeft4 = (int)((meanOrdinateLG2 + meanOrdinateLeft8) / 2);// 左边孔铜3纵坐标
            int middleRight = (dataArea2[0] + dataArea2[1]) / 2;// 右边面铜+基材铜横坐标
            int middleRight2 = (int)((meanOrdinateRight3 + meanOrdinateRG1) / 2);// 右边孔铜1纵坐标
            int middleRight3 = (int)((meanOrdinateRight5 + meanOrdinateRight6) / 2);// 右边孔铜2纵坐标
            int middleRight4 = (int)((meanOrdinateRG2 + meanOrdinateRight8) / 2);// 右边孔铜3纵坐标
            // 图一标记（左）
            // 上面铜
            SubFunction.LabelVertical(image, middleLeft + 40, (int)meanOrdinateLeft1, middleLeft + 40, (int)meanOrdinateLeft2, leftUpperMiantong);
            // 上基材铜
            SubFunction.LabelVertical(image, middleLeft - 40, (int)meanOrdinateLeft2, middleLeft - 40, (int)meanOrdinateLeft3, leftUpperJicaitong);
            // 上面铜+基材铜
            SubFunction.LabelVertical(image, middleLeft, (int)meanOrdinateLeft1, middleLeft, (int)meanOrdinateLeft3, leftUpperMian_Jicaitong);
            // 下面铜
            SubFunction.LabelVertical(image, middleLeft + 40, (int)meanOrdinateLeft9, middleLeft + 40, (int)meanOrdinateLeft10, leftLowerMiantong);
            // 下基材铜
            SubFunction.LabelVertical(image, middleLeft - 40, (int)meanOrdinateLeft8, middleLeft - 40, (int)meanOrdinateLeft9, leftLowerJicaitong);
            // 下面铜+基材铜
            SubFunction.LabelVertical(image, middleLeft, (int)meanOrdinateLeft8, middleLeft, (int)meanOrdinateLeft10, leftLowerMian_Jicaitong);
            // 孔铜
            SubFunction.LableHorizontal(image, (int)abscissaVLeft2, middleLeft2, (int)abscissaVLeft1, middleLeft2, leftKongtong1);
            SubFunction.LableHorizontal(image, (int)abscissaVLeft4, middleLeft3, (int)abscissaVLeft3, middleLeft3, leftKongtong2);
            SubFunction.LableHorizontal(image, (int)abscissaVLeft6, middleLeft4, (int)abscissaVLeft5, middleLeft4, leftKongtong3);

            // 图二标记（右）
            // 上面铜
            SubFunction.LabelVertical(image, middleRight + 40, (int)meanOrdinateRight1, middleRight + 40, (int)meanOrdinateRight2, rightUpperMiantong);
            // 上基材铜
            SubFunction.LabelVertical(image, middleRight - 40, (int)meanOrdinateRight2, middleRight - 40, (int)meanOrdinateRight3, rightUpperJicaitong);
            // 上面铜+基材铜
            SubFunction.LabelVertical(image, middleRight, (int)meanOrdinateRight1, middleRight, (int)meanOrdinateRight3, rightUpperMian_Jicaitong);
            // 下面铜
            SubFunction.LabelVertical(image, middleRight + 40, (int)meanOrdinateRight9, middleRight + 40, (int)meanOrdinateRight10, rightLowerMiantong);
            // 下基材铜
            SubFunction.LabelVertical(image, middleRight - 40, (int)meanOrdinateRight8, middleRight - 40, (int)meanOrdinateRight9, rightLowerJicaitong);
            // 下面铜+基材铜
            SubFunction.LabelVertical(image, middleRight, (int)meanOrdinateRight8, middleRight, (int)meanOrdinateRight10, rightLowerMian_Jicaitong);
            // 孔铜
            SubFunction.LableHorizontal(image, (int)abscissaVRight2, middleRight2, (int)abscissaVRight1, middleRight2, rightKongtong1);
            SubFunction.LableHorizontal(image, (int)abscissaVRight4, middleRight3, (int)abscissaVRight3, middleRight3, rightKongtong2);
            SubFunction.LableHorizontal(image, (int)abscissaVRight6, middleRight4, (int)abscissaVRight5, middleRight4, rightKongtong3);

            // 上孔径
            SubFunction.LableHorizontal(image, (int)abscissaVLeft2, (int)meanOrdinateLeft1, (int)abscissaVRight2, (int)meanOrdinateLeft1, upperKongjing);
            // 下孔径
            SubFunction.LableHorizontal(image, (int)abscissaVLeft6, (int)meanOrdinateLeft10, (int)abscissaVRight6, (int)meanOrdinateLeft10, lowerKongjing);
        }
        public static void CaokongShuangcengZhong(string fileName)
        {
            // 一、预处理
            // 读取图片
            Mat image = new Mat(fileName, ImreadModes.Color);

            //获取图片的长宽
            int rows = image.Rows;
            int cols = image.Cols;

            // 转换为灰度图
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);

            //获得蓝色，绿色，红色通道图片
            Mat imageBlue, imageGreen, imageRed = new Mat(imageGray.Size(), imageGray.Type());
            SubFunction.SeparateRGB(image, out imageBlue, out imageGreen, out imageRed);

            // 重新修改比例调色
            Mat imageNew = new Mat(imageRed.Size(),imageRed.Type());
            imageNew = 0.9 * imageGreen + 0.1 * imageRed;

            // 均值滤波
            Mat imageFilter = new Mat();
            Cv2.Blur(imageNew, imageFilter, new Size(5, 5));

            // 二值化，获得目标区域
            Mat imageContourText = imageFilter.Threshold(0, 255, ThresholdTypes.Otsu);// 用来计算消除亮光的边界
            Mat imageContour = imageRed.Threshold(0, 255, ThresholdTypes.Otsu);

            // 转成数组
            int[,] arrayContourText = BasFunction.Mat2Array(imageContourText);
            arrayContourText = BasFunction.ConversionRange(arrayContourText);

            // 将中间亮光置0
            int b2, b3;
            SubFunction.SplitArea(arrayContourText, out b2, out b3);
            Mat result = new Mat();
            BasFunction.SetNumber(imageContour, out result, 0, rows, b2, b3, 0);// 亮光区域置0
            imageContour = result;

            // 闭运算，消除小孔
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));// 结构元素
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Close, se);

            // 将原图分为两部分
            int dividingLine = (b2 + b3) / 2;
            Mat imageContour1 = imageContour;
            Mat imageContour2 = imageContour;
            for (int i = 0; i < rows; i++)
            {
                for (int j = 0; j < dividingLine; j++)
                {
                    imageContour2.Set<int>(i, j, 0);
                }
                for (int k = dividingLine; k < cols; k++)
                {
                    imageContour1.Set<int>(i, k, 0);
                }
            }

            // 边缘检测
            Mat imageOutline1;
            Mat imageOutline2;
            SubFunction.Sobel(imageContour1, out imageOutline1);
            SubFunction.Sobel(imageContour2, out imageOutline2);

            // 转成数组
            int[,] arrayOutline1 = BasFunction.Mat2Array(imageOutline1);
            arrayOutline1 = BasFunction.ConversionRange(arrayOutline1);
            int[,] arrayOutline2 = BasFunction.Mat2Array(imageOutline2);
            arrayOutline2 = BasFunction.ConversionRange(arrayOutline2);

            // 计算图像1（左）
            // 二、计算数据提取区域
            // 对图片进行填充 
            Mat imageFill = new Mat();
            SubFunction.Fill(imageContour1, out imageFill);

            // 计算数据提取区域
            int[] dataArea = new int[2];
            SubFunction.DataArea2(imageFill, out dataArea);

            // 三、提取L1，L3，L4，L6
            double meanOrdinateLeft1 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft1, dataArea[0], dataArea[1]);
            double meanOrdinateLeft3 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft3, dataArea[0], dataArea[1], meanOrdinateLeft1);
            double meanOrdinateLeft4 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft4, dataArea[0], dataArea[1], meanOrdinateLeft3);
            double meanOrdinateLeft6 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft6, dataArea[0], dataArea[1], meanOrdinateLeft4);

            // 四、提取L2
            double meanOrdinateLeft2 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateLeft1 + 10, (int)meanOrdinateLeft3 - 10, dataArea[0], dataArea[1], out meanOrdinateLeft2);

            // 五、提取L5
            double meanOrdinateLeft5 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateLeft4 + 10, (int)meanOrdinateLeft6 - 10, dataArea[0], dataArea[1], out meanOrdinateLeft5);

            // 六、提竖线V1,V2
            double abscissaVLeft1 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline1, out abscissaVLeft1, (int)meanOrdinateLeft3, (int)meanOrdinateLeft4);
            double abscissaVLeft2 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline1, out abscissaVLeft2, (int)meanOrdinateLeft3, (int)meanOrdinateLeft4, abscissaVLeft1);

            // 计算图像2（右）
            // 二、计算数据提取区域
            // 对图片进行填充 
            Mat imageFill2 = new Mat();
            SubFunction.Fill(imageContour2, out imageFill);

            // 计算数据提取区域
            int[] dataArea2 = new int[2];
            SubFunction.DataArea2(imageFill2, out dataArea2);

            // 三、提取L1，L3，L4，L6
            double meanOrdinateRight1 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight1, dataArea2[0], dataArea2[1]);
            double meanOrdinateRight3 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight3, dataArea2[0], dataArea2[1], meanOrdinateRight1);
            double meanOrdinateRight4 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight4, dataArea2[0], dataArea2[1], meanOrdinateRight3);
            double meanOrdinateRight6 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight6, dataArea2[0], dataArea2[1], meanOrdinateRight4);

            // 四、提取L2
            double meanOrdinateRight2 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateRight1 + 10, (int)meanOrdinateRight3 - 10, dataArea2[0], dataArea2[1], out meanOrdinateRight2);

            // 五、提取L5
            double meanOrdinateRight5 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateRight4 + 10, (int)meanOrdinateRight6 - 10, dataArea2[0], dataArea2[1], out meanOrdinateRight5);

            // 六、提竖线V1,V2
            double abscissaVRight1 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline2, out abscissaVRight1, (int)meanOrdinateRight3, (int)meanOrdinateRight4);
            double abscissaVRight2 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline2, out abscissaVRight2, (int)meanOrdinateRight3, (int)meanOrdinateRight4, abscissaVRight1);

            // 七、提取上孔径
            double kongjingLeft1 = 0;
            double kongjingLeft2 = 0;
            double kongjingRight1 = 0;
            double kongjingRight2 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline1, out kongjingLeft1, (int)meanOrdinateLeft3, (int)meanOrdinateLeft3 + 20);
            SubFunction.ExtractVerticalLines(arrayOutline1, out kongjingLeft2, (int)meanOrdinateLeft3, (int)meanOrdinateLeft3 + 20, kongjingLeft1);
            SubFunction.ExtractVerticalLines2(arrayOutline2, out kongjingRight1, (int)meanOrdinateRight3, (int)meanOrdinateRight3 + 20);
            SubFunction.ExtractVerticalLines2(arrayOutline2, out kongjingRight2, (int)meanOrdinateRight3, (int)meanOrdinateRight3 + 20, kongjingRight1);

            // 八、提取下孔径
            double kongjingLeft3 = 0;
            double kongjingLeft4 = 0;
            double kongjingRight3 = 0;
            double kongjingRight4 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline1, out kongjingLeft3, (int)meanOrdinateLeft4 - 20, (int)meanOrdinateLeft4);
            SubFunction.ExtractVerticalLines(arrayOutline1, out kongjingLeft4, (int)meanOrdinateLeft4 - 20, (int)meanOrdinateLeft4, kongjingLeft3);
            SubFunction.ExtractVerticalLines2(arrayOutline2, out kongjingRight3, (int)meanOrdinateRight4 - 20, (int)meanOrdinateRight4);
            SubFunction.ExtractVerticalLines2(arrayOutline2, out kongjingRight4, (int)meanOrdinateRight4 - 20, (int)meanOrdinateRight4, kongjingRight3);
            // 七、数据计算
            // 左
            double leftUpperMiantong = meanOrdinateLeft2 - meanOrdinateLeft1;
            double leftUpperJicaitong = meanOrdinateLeft3 - meanOrdinateLeft2;
            double leftUpperMian_Jicaitong = meanOrdinateLeft3 - meanOrdinateLeft1;
            double leftLowerMiantong = meanOrdinateLeft6 - meanOrdinateLeft5;
            double leftLowerJicaitong = meanOrdinateLeft5 - meanOrdinateLeft4;
            double leftLowerMian_Jicaitong = meanOrdinateLeft6 - meanOrdinateLeft4;
            double leftKongtong = abscissaVLeft1 - abscissaVLeft2;
            // 右
            double rightUpperMiantong = meanOrdinateRight2 - meanOrdinateRight1;
            double rightUpperJicaitong = meanOrdinateRight3 - meanOrdinateRight2;
            double rightUpperMian_Jicaitong = meanOrdinateRight3 - meanOrdinateRight1;
            double rightLowerMiantong = meanOrdinateRight6 - meanOrdinateRight5;
            double rightLowerJicaitong = meanOrdinateRight5 - meanOrdinateRight4;
            double rightLowerMian_Jicaitong = meanOrdinateRight6 - meanOrdinateRight4;
            double rightKongtong = abscissaVRight2 - abscissaVRight1;

            double upperKongjing = kongjingRight2 - kongjingLeft2;
            double lowerKongjing = kongjingRight4 - kongjingLeft4;

            // 八、标记
            int middleLeft = (dataArea[0] + dataArea[1]) / 2;
            int middleLeft2 = (int)((meanOrdinateLeft3 + meanOrdinateLeft4) / 2);
            int middleRight = (dataArea2[0] + dataArea2[1]) / 2;
            int middleRight2 = (int)((meanOrdinateRight3 + meanOrdinateRight4) / 2);
            // 图一标记（左）
            // 上面铜
            SubFunction.LabelVertical(image, middleLeft + 40, (int)meanOrdinateLeft1, middleLeft + 40, (int)meanOrdinateLeft2, leftUpperMiantong);
            // 上基材铜
            SubFunction.LabelVertical(image, middleLeft - 40, (int)meanOrdinateLeft2, middleLeft - 40, (int)meanOrdinateLeft3, leftUpperJicaitong);
            // 上面铜+基材铜
            SubFunction.LabelVertical(image, middleLeft, (int)meanOrdinateLeft1, middleLeft, (int)meanOrdinateLeft3, leftUpperMian_Jicaitong);
            // 下面铜
            SubFunction.LabelVertical(image, middleLeft + 40, (int)meanOrdinateLeft5, middleLeft + 40, (int)meanOrdinateLeft6, leftLowerMiantong);
            // 下基材铜
            SubFunction.LabelVertical(image, middleLeft - 40, (int)meanOrdinateLeft4, middleLeft - 40, (int)meanOrdinateLeft5, leftLowerJicaitong);
            // 下面铜+基材铜
            SubFunction.LabelVertical(image, middleLeft, (int)meanOrdinateLeft4, middleLeft, (int)meanOrdinateLeft6, leftLowerMian_Jicaitong);
            // 孔铜
            SubFunction.LableHorizontal(image, (int)abscissaVLeft2, middleLeft2, (int)abscissaVLeft1, middleLeft2, leftKongtong);
            
            // 图二标记（右）
            // 上面铜
            SubFunction.LabelVertical(image, middleRight + 40, (int)meanOrdinateRight1, middleRight + 40, (int)meanOrdinateRight2, rightUpperMiantong);
            // 上基材铜
            SubFunction.LabelVertical(image, middleRight - 40, (int)meanOrdinateRight2, middleRight - 40, (int)meanOrdinateRight3, rightUpperJicaitong);
            // 上面铜+基材铜
            SubFunction.LabelVertical(image, middleRight, (int)meanOrdinateRight1, middleRight, (int)meanOrdinateRight3, rightUpperMian_Jicaitong);
            // 下面铜
            SubFunction.LabelVertical(image, middleRight + 40, (int)meanOrdinateRight5, middleRight + 40, (int)meanOrdinateRight6, rightLowerMiantong);
            // 下基材铜
            SubFunction.LabelVertical(image, middleRight - 40, (int)meanOrdinateRight4, middleRight - 40, (int)meanOrdinateRight5, rightLowerJicaitong);
            // 下面铜+基材铜
            SubFunction.LabelVertical(image, middleRight, (int)meanOrdinateRight4, middleRight, (int)meanOrdinateRight6, rightLowerMian_Jicaitong);
            // 孔铜
            SubFunction.LableHorizontal(image, (int)abscissaVRight2, middleRight2, (int)abscissaVRight1, middleRight2, rightKongtong);

            // 上孔径
            SubFunction.LableHorizontal(image, (int)kongjingLeft2, (int)meanOrdinateLeft1, (int)kongjingRight2, (int)meanOrdinateLeft1, upperKongjing);
            // 下孔径
            SubFunction.LableHorizontal(image, (int)kongjingLeft4, (int)meanOrdinateLeft6, (int)kongjingRight4, (int)meanOrdinateLeft6, lowerKongjing);
        }
        public static void CaokongSancengZhong(string fileName)
        {
            // 一、预处理
            // 读取图片
            Mat image = new Mat(fileName, ImreadModes.Color);

            //获取图片的长宽
            int rows = image.Rows;
            int cols = image.Cols;

            // 转换为灰度图
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);

            //获得蓝色，绿色，红色通道图片
            Mat imageBlue, imageGreen, imageRed = new Mat(imageGray.Size(), imageGray.Type());
            SubFunction.SeparateRGB(image, out imageBlue, out imageGreen, out imageRed);

            // 重新修改比例调色
            Mat imageNew = new Mat(imageRed.Size(), imageRed.Type());
            imageNew = 0.9 * imageGreen + 0.1 * imageRed;

            // 均值滤波
            Mat imageFilter = new Mat();
            Cv2.Blur(imageNew, imageFilter, new Size(5, 5));

            // 二值化，获得目标区域
            Mat imageContourText = imageFilter.Threshold(0, 255, ThresholdTypes.Otsu);// 用来计算消除亮光的边界
            Mat imageContour = imageRed.Threshold(0, 255, ThresholdTypes.Otsu);

            // 转成数组
            int[,] arrayContourText = BasFunction.Mat2Array(imageContourText);
            arrayContourText = BasFunction.ConversionRange(arrayContourText);

            // 将中间亮光置0
            int b2, b3;
            SubFunction.SplitArea(arrayContourText, out b2, out b3);
            Mat result = new Mat();
            BasFunction.SetNumber(imageContour, out result, 0, rows, b2, b3, 0);// 亮光区域置0
            imageContour = result;

            // 闭运算，消除小孔
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));// 结构元素
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Close, se);

            // 将原图分为两部分
            int dividingLine = (b2 + b3) / 2;
            Mat imageContour1 = imageContour;
            Mat imageContour2 = imageContour;
            for (int i = 0; i < rows; i++)
            {
                for (int j = 0; j < dividingLine; j++)
                {
                    imageContour2.Set<int>(i, j, 0);
                }
                for (int k = dividingLine; k < cols; k++)
                {
                    imageContour1.Set<int>(i, k, 0);
                }
            }

            // 边缘检测
            Mat imageOutline1;
            Mat imageOutline2;
            SubFunction.Sobel(imageContour1, out imageOutline1);
            SubFunction.Sobel(imageContour2, out imageOutline2);

            // 转成数组
            int[,] arrayOutline1 = BasFunction.Mat2Array(imageOutline1);
            arrayOutline1 = BasFunction.ConversionRange(arrayOutline1);
            int[,] arrayOutline2 = BasFunction.Mat2Array(imageOutline2);
            arrayOutline2 = BasFunction.ConversionRange(arrayOutline2);

            // 计算图像1（左）
            // 二、计算数据提取区域
            // 对图片进行填充 
            Mat imageFill = new Mat();
            SubFunction.Fill(imageContour1, out imageFill);

            // 计算数据提取区域
            int[] dataArea = new int[2];
            SubFunction.DataArea2(imageFill, out dataArea);

            // 三、提取L1，L3，L4，L5, L6, L8
            double meanOrdinateLeft1 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft1, dataArea[0], dataArea[1]);
            double meanOrdinateLeft3 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft3, dataArea[0], dataArea[1], meanOrdinateLeft1);
            double meanOrdinateLeft4 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft4, dataArea[0], dataArea[1], meanOrdinateLeft3);
            double meanOrdinateLeft5 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft5, dataArea[0], dataArea[1], meanOrdinateLeft4);
            double meanOrdinateLeft6 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft6, dataArea[0], dataArea[1], meanOrdinateLeft5);
            double meanOrdinateLeft8 = 0;
            SubFunction.ExtractLines(arrayOutline1, out meanOrdinateLeft8, dataArea[0], dataArea[1], meanOrdinateLeft6);

            // 四、提取L2
            double meanOrdinateLeft2 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateLeft1 + 10, (int)meanOrdinateLeft3 - 10, dataArea[0], dataArea[1], out meanOrdinateLeft2);

            // 五、提取L7
            double meanOrdinateLeft7 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateLeft6 + 10, (int)meanOrdinateLeft8 - 10, dataArea[0], dataArea[1], out meanOrdinateLeft7);

            // 六、提取胶体线
            Mat imageGlue = new Mat();
            SubFunction.GlueArea(imageContour1, imageRed, out imageGlue, (int)meanOrdinateLeft5 + 10, (int)meanOrdinateLeft6 - 10, dataArea[0], dataArea[1]);

            // 转数组
            int[,] arrayGlue = BasFunction.Mat2Array(imageGlue);
            arrayGlue = BasFunction.ConversionRange(arrayGlue);

            // 提取胶体线
            double meanOrdinateLG = 0;
            SubFunction.InsideLine(imageGlue, (int)meanOrdinateLeft5 + 15, (int)meanOrdinateLeft6 - 15, dataArea[0], dataArea[1], out meanOrdinateLG);
            
            // 七、提竖线V1,V2, V3, V4
            double abscissaVLeft1 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline1, out abscissaVLeft1, (int)meanOrdinateLeft3, (int)meanOrdinateLeft4);
            double abscissaVLeft2 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline1, out abscissaVLeft2, (int)meanOrdinateLeft3, (int)meanOrdinateLeft4, abscissaVLeft1);
            double abscissaVLeft3 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline1, out abscissaVLeft3, (int)meanOrdinateLG, (int)meanOrdinateLeft6);
            double abscissaVLeft4 = 0;
            SubFunction.ExtractVerticalLines(arrayOutline1, out abscissaVLeft4, (int)meanOrdinateLG, (int)meanOrdinateLeft6, abscissaVLeft3);

            // 八、计算粗糙度
            int cucaoduLeft = 0;
            int[] cucaoduZuobiaoLeft = new int[2];
            SubFunction.Cucaodu(arrayOutline1, (int)meanOrdinateLeft5 + 60, (int)meanOrdinateLeft6 - 30, (int)abscissaVLeft4, out cucaoduLeft, out cucaoduZuobiaoLeft);

            // 计算图像2（右）
            // 二、计算数据提取区域
            // 对图片进行填充 
            Mat imageFill2 = new Mat();
            SubFunction.Fill(imageContour2, out imageFill);

            // 计算数据提取区域
            int[] dataArea2 = new int[2];
            SubFunction.DataArea2(imageFill2, out dataArea2);

            // 三、提取L1，L3，L4，L5, L6, L8
            double meanOrdinateRight1 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight1, dataArea2[0], dataArea2[1]);
            double meanOrdinateRight3 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight3, dataArea2[0], dataArea2[1], meanOrdinateRight1);
            double meanOrdinateRight4 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight4, dataArea2[0], dataArea2[1], meanOrdinateRight3);
            double meanOrdinateRight5 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight5, dataArea2[0], dataArea2[1], meanOrdinateRight4);
            double meanOrdinateRight6 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight6, dataArea2[0], dataArea2[1], meanOrdinateRight5);
            double meanOrdinateRight8 = 0;
            SubFunction.ExtractLines(arrayOutline2, out meanOrdinateRight8, dataArea2[0], dataArea2[1], meanOrdinateRight6);

            // 四、提取L2
            double meanOrdinateRight2 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateRight1 + 10, (int)meanOrdinateRight3 - 10, dataArea2[0], dataArea2[1], out meanOrdinateRight2);

            // 五、提取L5
            double meanOrdinateRight7 = 0;
            SubFunction.InsideLine(imageGreen, (int)meanOrdinateRight6 + 10, (int)meanOrdinateRight8 - 10, dataArea2[0], dataArea2[1], out meanOrdinateRight7);

            // 六、提取胶体线
            Mat imageGlue2 = new Mat();
            SubFunction.GlueArea(imageContour2, imageRed, out imageGlue2, (int)meanOrdinateRight5 + 10, (int)meanOrdinateRight6 - 10, dataArea2[0], dataArea2[1]);

            // 转数组
            int[,] arrayGlue2 = BasFunction.Mat2Array(imageGlue2);
            arrayGlue2 = BasFunction.ConversionRange(arrayGlue2);

            // 提取胶体线
            double meanOrdinateRG = 0;
            SubFunction.InsideLine(imageGlue, (int)meanOrdinateRight5 + 15, (int)meanOrdinateRight6 - 15, dataArea2[0], dataArea2[1], out meanOrdinateRG);
           
            // 七 、提竖线V1,V2, V3, V4
            double abscissaVRight1 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline2, out abscissaVRight1, (int)meanOrdinateRight3, (int)meanOrdinateRight4);
            double abscissaVRight2 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline2, out abscissaVRight2, (int)meanOrdinateRight3, (int)meanOrdinateRight4, abscissaVRight1);
            double abscissaVRight3 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline2, out abscissaVRight3, (int)meanOrdinateRG, (int)meanOrdinateRight6);
            double abscissaVRight4 = 0;
            SubFunction.ExtractVerticalLines2(arrayOutline2, out abscissaVRight4, (int)meanOrdinateRG, (int)meanOrdinateRight6, abscissaVRight3);

            // 八、计算粗糙度
            int cucaoduRight = 0;
            int[] cucaoduZuobiaoRight = new int[2];
            SubFunction.Cucaodu(arrayOutline2, (int)meanOrdinateRight5 + 60, (int)meanOrdinateRight6 - 30, (int)abscissaVRight4, out cucaoduRight, out cucaoduZuobiaoRight);

            
            // 九、数据计算
            // 左
            double leftUpperMiantong = meanOrdinateLeft2 - meanOrdinateLeft1;
            double leftUpperJicaitong = meanOrdinateLeft3 - meanOrdinateLeft2;
            double leftUpperMian_Jicaitong = meanOrdinateLeft3 - meanOrdinateLeft1;
            double leftLowerMiantong = meanOrdinateLeft6 - meanOrdinateLeft5;
            double leftLowerJicaitong = meanOrdinateLeft5 - meanOrdinateLeft4;
            double leftLowerMian_Jicaitong = meanOrdinateLeft6 - meanOrdinateLeft4;
            double leftKongtong1 = abscissaVLeft1 - abscissaVLeft2;
            double leftKongtong2 = abscissaVLeft3 - abscissaVLeft4;
            // 右
            double rightUpperMiantong = meanOrdinateRight2 - meanOrdinateRight1;
            double rightUpperJicaitong = meanOrdinateRight3 - meanOrdinateRight2;
            double rightUpperMian_Jicaitong = meanOrdinateRight3 - meanOrdinateRight1;
            double rightLowerMiantong = meanOrdinateRight6 - meanOrdinateRight5;
            double rightLowerJicaitong = meanOrdinateRight5 - meanOrdinateRight4;
            double rightLowerMian_Jicaitong = meanOrdinateRight6 - meanOrdinateRight4;
            double rightKongtong1 = abscissaVRight2 - abscissaVRight1;
            double rightKongtong2 = abscissaVRight4 - abscissaVRight3;

            double upperKongjing = abscissaVRight2 - abscissaVLeft2; ;
            double lowerKongjing = abscissaVRight4 - abscissaVLeft4;

            // 八、标记
            int middleLeft = (dataArea[0] + dataArea[1]) / 2;// 左面铜+基材铜横坐标
            int middleLeft2 = (int)((meanOrdinateLeft3 + meanOrdinateLeft4) / 2);// 左孔铜1纵坐标
            int middleLeft3 = (int)((meanOrdinateLG + meanOrdinateLeft6) / 2);// 左孔铜2纵坐标
            int middleRight = (dataArea2[0] + dataArea2[1]) / 2;// 右面铜+基材铜横坐标
            int middleRight2 = (int)((meanOrdinateRight3 + meanOrdinateRight4) / 2);// 右孔铜1纵坐标
            int middleRight3 = (int)((meanOrdinateRG + meanOrdinateRight6) / 2);// 右孔铜2纵坐标
            // 图一标记（左）
            // 上面铜
            SubFunction.LabelVertical(image, middleLeft + 40, (int)meanOrdinateLeft1, middleLeft + 40, (int)meanOrdinateLeft2, leftUpperMiantong);
            // 上基材铜
            SubFunction.LabelVertical(image, middleLeft - 40, (int)meanOrdinateLeft2, middleLeft - 40, (int)meanOrdinateLeft3, leftUpperJicaitong);
            // 上面铜+基材铜
            SubFunction.LabelVertical(image, middleLeft, (int)meanOrdinateLeft1, middleLeft, (int)meanOrdinateLeft3, leftUpperMian_Jicaitong);
            // 下面铜
            SubFunction.LabelVertical(image, middleLeft + 40, (int)meanOrdinateLeft5, middleLeft + 40, (int)meanOrdinateLeft6, leftLowerMiantong);
            // 下基材铜
            SubFunction.LabelVertical(image, middleLeft - 40, (int)meanOrdinateLeft4, middleLeft - 40, (int)meanOrdinateLeft5, leftLowerJicaitong);
            // 下面铜+基材铜
            SubFunction.LabelVertical(image, middleLeft, (int)meanOrdinateLeft4, middleLeft, (int)meanOrdinateLeft6, leftLowerMian_Jicaitong);
            // 孔铜
            SubFunction.LableHorizontal(image, (int)abscissaVLeft2, middleLeft2, (int)abscissaVLeft1, middleLeft2, leftKongtong1);
            SubFunction.LableHorizontal(image, (int)abscissaVLeft4, middleLeft3, (int)abscissaVLeft3, middleLeft3, leftKongtong2);

            // 图二标记（右）
            // 上面铜
            SubFunction.LabelVertical(image, middleRight + 40, (int)meanOrdinateRight1, middleRight + 40, (int)meanOrdinateRight2, rightUpperMiantong);
            // 上基材铜
            SubFunction.LabelVertical(image, middleRight - 40, (int)meanOrdinateRight2, middleRight - 40, (int)meanOrdinateRight3, rightUpperJicaitong);
            // 上面铜+基材铜
            SubFunction.LabelVertical(image, middleRight, (int)meanOrdinateRight1, middleRight, (int)meanOrdinateRight3, rightUpperMian_Jicaitong);
            // 下面铜
            SubFunction.LabelVertical(image, middleRight + 40, (int)meanOrdinateRight5, middleRight + 40, (int)meanOrdinateRight6, rightLowerMiantong);
            // 下基材铜
            SubFunction.LabelVertical(image, middleRight - 40, (int)meanOrdinateRight4, middleRight - 40, (int)meanOrdinateRight5, rightLowerJicaitong);
            // 下面铜+基材铜
            SubFunction.LabelVertical(image, middleRight, (int)meanOrdinateRight4, middleRight, (int)meanOrdinateRight6, rightLowerMian_Jicaitong);
            // 孔铜
            SubFunction.LableHorizontal(image, (int)abscissaVRight2, middleRight2, (int)abscissaVRight1, middleRight2, rightKongtong1);
            SubFunction.LableHorizontal(image, (int)abscissaVRight4, middleRight3, (int)abscissaVRight3, middleRight3, rightKongtong2);

            // 上孔径
            SubFunction.LableHorizontal(image, (int)abscissaVLeft2, (int)meanOrdinateLeft1, (int)abscissaVRight2, (int)meanOrdinateLeft1, upperKongjing);
            // 下孔径
            SubFunction.LableHorizontal(image, (int)abscissaVLeft4, (int)meanOrdinateLeft6, (int)abscissaVRight4, (int)meanOrdinateLeft6, lowerKongjing); 
        }
        public static void ShikeyinziDanceng(string fileName)
        {
            // 一、预处理
            // 读取图片
            Mat image = new Mat(fileName, ImreadModes.Color);

            //获取图片的长宽
            int rows = image.Rows;
            int cols = image.Cols;

            // 转换为灰度图
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);

            //获得蓝色，绿色，红色通道图片
            Mat imageBlue, imageGreen, imageRed = new Mat(imageGray.Size(), imageGray.Type());
            SubFunction.SeparateRGB(image, out imageBlue, out imageGreen, out imageRed);

            // 二值化，获得目标区域
            Mat imageContour = imageGray.Threshold(0, 255, ThresholdTypes.Otsu);
            // 闭运算，消除小孔
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));// 结构元素
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Close, se);

            // 转成数组
            int[,] arrayContour = BasFunction.Mat2Array(imageContour);
            arrayContour = BasFunction.ConversionRange(arrayContour);

            // 选定检测区域
            int[] dataArea = new int[4];
            SubFunction.SKYZDataArea(imageContour, out dataArea);

            // 截取检测区域
            int[,] arrayData = BasFunction.InterceptArray(arrayContour, dataArea[0], dataArea[1], dataArea[2], dataArea[3]);

            // 计算上横线位置
            int[] upperX = new int[2];
            SubFunction.UpperLine(arrayData, dataArea, out upperX);

            // 计算上、下顶点坐标
            int upperY;
            int lowerY;
            SubFunction.LowerLine(arrayData,(dataArea[3]-dataArea[2])/2, out upperY,out lowerY);

            // 计算数据
            int shangfu = upperX[1] - upperX[0];
            int xiafu = dataArea[3] - dataArea[2];
            int tonghou = lowerY - upperY;

            // 标记
            // 上幅
            SubFunction.LableHorizontal(image, upperX[0]+dataArea[2], upperY+dataArea[0] - 10, upperX[1] + dataArea[2], upperY + dataArea[0] - 10, shangfu);
            // 下幅
            SubFunction.LableHorizontal(image, dataArea[2], lowerY + dataArea[0] + 10, dataArea[3], lowerY + dataArea[0] + 10, xiafu);
            // 铜厚
            int middle = (upperX[0] + upperX[1]) / 2;
            SubFunction.LabelVertical(image, middle + dataArea[2], upperY + dataArea[0], middle + dataArea[2], lowerY + dataArea[0], tonghou);

            // 保存
            Cv2.ImWrite(@"D:\蚀刻因子单层.jpg",image);
            // 显示
            new Window("demo1", WindowMode.Normal, image);
            Cv2.WaitKey(0);
        }
        public static void ShikeyinziShuangceng(string fileName) 
        {
            // 一、预处理
            // 读取图片
            Mat image = new Mat(fileName, ImreadModes.Color);

            //获取图片的长宽
            int rows = image.Rows;
            int cols = image.Cols;

            // 转换为灰度图
            Mat imageGray = image.CvtColor(ColorConversionCodes.BGR2GRAY);

            //获得蓝色，绿色，红色通道图片
            Mat imageBlue, imageGreen, imageRed = new Mat(imageGray.Size(), imageGray.Type());
            SubFunction.SeparateRGB(image, out imageBlue, out imageGreen, out imageRed);

            // 二值化，获得目标区域
            Mat imageContour = imageGray.Threshold(0, 255, ThresholdTypes.Otsu);
            // 闭运算，消除小孔
            Mat se = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));// 结构元素
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Close, se);
            // 开运算，去除小面积
            Mat se2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Cv2.MorphologyEx(imageContour, imageContour, MorphTypes.Open, se2);

            // 转成数组 
            int[,] arrayContour = BasFunction.Mat2Array(imageContour);
            arrayContour = BasFunction.ConversionRange(arrayContour);

            // 选定检测区域
            int[] dataArea = new int[4];
            SubFunction.SKYZDataArea(imageContour, out dataArea);

            // 截取检测区域
            int[,] arrayData = BasFunction.InterceptArray(arrayContour, dataArea[0], dataArea[1], dataArea[2], dataArea[3]);

            // 计算上横线位置
            int[] upperX = new int[2];
            SubFunction.UpperLine(arrayData, dataArea, out upperX);

            // 计算上、下顶点坐标
            int upperY;
            int lowerY;
            SubFunction.LowerLine(arrayData,100, out upperY, out lowerY);

            // 提取内部线
            double insideY = 0;
            SubFunction.InsideLine(imageGreen, upperY + 30+dataArea[0], lowerY - 50+dataArea[0], dataArea[2]+20, dataArea[3]-20, out insideY);

            // 计算数据
            int shangfu = upperX[1] - upperX[0];
            int xiafu = dataArea[3] - dataArea[2];
            int tonghou = lowerY+dataArea[0] - (int)insideY;
            int zonghou = lowerY - upperY;

            // 标记
            // 上幅
            SubFunction.LableHorizontal(image, upperX[0]+dataArea[2], upperY - 10+dataArea[0], upperX[1] + dataArea[2], upperY - 10 + dataArea[0], shangfu);
            // 下幅
            SubFunction.LableHorizontal(image, dataArea[2], lowerY + 10 + dataArea[0], dataArea[3], lowerY + 10 + dataArea[0], xiafu);
            // 总厚
            int middle = (upperX[0] + upperX[1]) / 2;
            SubFunction.LabelVertical(image, dataArea[2]+100, upperY + dataArea[0], dataArea[2]+100, lowerY + dataArea[0], zonghou);
            // 铜厚
            SubFunction.LabelVertical(image, dataArea[3]-100, (int)insideY , dataArea[3]-100, lowerY + dataArea[0], tonghou);

            // 保存
            Cv2.ImWrite(@"D:\蚀刻因子双层.jpg", image);
            // 显示
            new Window("demo1", WindowMode.Normal, image);
            Cv2.WaitKey(0);
        }

    } 
}