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@@ -15,6 +15,8 @@ using SmartSEMControl;
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using MeasureData;
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using FileManager;
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+using OpenCvSharp;
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+
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namespace MeasureThread
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{
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//图片模式
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@@ -468,6 +470,12 @@ namespace MeasureThread
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}
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public void SendMsg(string step_code)
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+ {
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+ arg.State = step_code;
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+ SendThreadStatus(this, arg);
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+ }
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+
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+ public void SendMsg1(string step_code)
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{
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arg.Step_Code = step_code;
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arg.Time = DateTime.Now;
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@@ -1641,26 +1649,270 @@ namespace MeasureThread
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return false;
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}
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+ string path = a_param.Path;
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+ if (!Directory.Exists(path))
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+ {
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+ return false;
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+ }
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+ string path_coarse = a_param.Path + "\\Coarse";
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+ if (!Directory.Exists(path_coarse))
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+ {
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+ Directory.CreateDirectory(path_coarse);
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+ }
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+ string path_fine = a_param.Path + "\\Fine";
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+ if (!Directory.Exists(path_fine))
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+ {
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+ Directory.CreateDirectory(path_fine);
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+ }
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+
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+
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//1. 拍照
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- //1.1， 初拍照
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+ //1.1， 粗拍照
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//1.1.1， 根据参数计算拍照次数
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- //int n =
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+ double nUp = a_param.UP * 100.0 ;
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+ double nDown = a_param.Down * 100.0;
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+ double nStep = a_param.Step * 100.0;
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+ double nTimes = Math.Ceiling((nDown - nUp) / nStep + 0.5);
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+
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+ SendMsg("粗对焦:最小值" + nUp.ToString() + ",最大值" + nDown.ToString() + ",步长" + nStep.ToString() + "拍照张数" + nTimes.ToString());
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- //3.控制SEM拍照
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- String fileName4 = WorkingFolder + ImageName4;
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- if (!GetImage(ImageMode.SEM, fileName4))
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+ //粗拍照
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+ for (int i = 0; i < nTimes; i++)
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{
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- return false;
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+
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+ int cWd =(int) Math.Ceiling(nUp + i * nStep + 0.5);
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+ iSEM.SetWorkingDistance((float)(cWd * 0.00000001));
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+ Thread.Sleep(3000);
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+
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+ int swd = cWd / 100;
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+ SendMsg("wd = " + swd.ToString() +"um");
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+
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+ String fileName = path_coarse + "\\" + cWd.ToString() + ".tif";
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+ if (!GetImage(ImageMode.SEM, fileName))
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+ {
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+ return false;
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+ }
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+
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+ Thread.Sleep(5000);
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}
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//1.2， 选定细拍照的工作距离
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+ int CorWd;
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+ ChooseBest(path_coarse,out CorWd);
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+
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+ a_nWd = CorWd;
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+
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+ SendMsg("粗选工作距离wd = " + a_nWd.ToString() );
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+
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+
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//1.3， 细拍照
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+ if ( (CorWd - a_param.Range * 100.0) <=0)
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+ {
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+ return false;
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+ }
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+
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+ double nfUp = CorWd - a_param.Range * 100.0;
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+ double nfStep = a_param.fStep * 100.0;
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+ double nfTimes = Math.Ceiling((a_param.Range * 100.0 * 2) / nfStep + 0.5);
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+
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+
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+ SendMsg("粗对焦:最小值" + nfUp.ToString() + ",步长" + nfStep.ToString() + "拍照张数" + nfTimes.ToString());
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+
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+
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+ for (int i = 0; i < nfTimes; i++)
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+ {
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+ int cWd = (int)Math.Ceiling(nfUp + i * nfStep + 0.5);
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+ iSEM.SetWorkingDistance((float)(cWd * 0.00000001));
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+ Thread.Sleep(3000);
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+
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+ int swd = cWd / 100;
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+ SendMsg("wd = " + swd.ToString() + "um");
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+
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+ String fileName = path_fine + "\\" + cWd.ToString() + ".tif";
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+ if (!GetImage(ImageMode.SEM, fileName))
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+ {
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+ return false;
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+ }
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+
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+ Thread.Sleep(5000);
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+ }
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+
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+ int fineWd;
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+ ChooseBest(path_coarse, out fineWd);
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+
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+ SendMsg("wd fine max = " + fineWd.ToString());
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+
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+ a_nWd = fineWd;
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- //2. 计算评价函数
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+ SendMsg("细选工作距离wd = " + a_nWd.ToString());
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- //3. 3选2策略获取工作距离
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return true;
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}
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+
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+ //LoG算子计算
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+ private double LoGMean(string a_strImgPath)
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+ {
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+ //读入Img文件
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+ if (!File.Exists(a_strImgPath))
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+ {
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+ return 0;
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+ }
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+
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+ Mat src, gray_src;
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+ int kernel_size = 3;
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+
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+ src = Cv2.ImRead(a_strImgPath);
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+ gray_src = new Mat();
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+
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+ src.CvtColor(ColorConversionCodes.BGR2GRAY);
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+
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+ Mat kernel = Cv2.GetStructuringElement(MorphShapes.Cross, new OpenCvSharp.Size(10, 10));
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+ Cv2.MorphologyEx(src, src, MorphTypes.Close, kernel);
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+
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+ Cv2.GaussianBlur(src, src, new OpenCvSharp.Size(3, 3), 0, 0);
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+ Cv2.Laplacian(src, src, MatType.CV_8UC3, kernel_size);
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+ Cv2.ConvertScaleAbs(src, src);
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+
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+ //图像的平均灰度
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+
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+ double meanValue = 0.0;
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+ meanValue = Cv2.Mean(src)[0];
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+ return meanValue;
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+ }
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+
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+ //梯度计算
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+ private double Tenengrad(string a_strImgPath)
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+ {
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+ //读入Img文件
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+ if (!File.Exists(a_strImgPath))
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+ {
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+ return 0;
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+ }
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+
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+ Mat src;
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+ src = Cv2.ImRead(a_strImgPath);
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+
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+ src.CvtColor(ColorConversionCodes.BGR2GRAY);
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+
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+ Mat kernel = Cv2.GetStructuringElement(MorphShapes.Cross, new OpenCvSharp.Size(10, 10));
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+ Cv2.MorphologyEx(src, src, MorphTypes.Close, kernel);
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+
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+ Cv2.GaussianBlur(src, src, new OpenCvSharp.Size(3, 3), 0, 0);
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+ Cv2.Sobel(src, src, MatType.CV_8UC1, 1, 1);
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+ //图像的平均灰度
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+ double meanValue = 0.0;
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+ meanValue = Cv2.Mean(src)[0];
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+ return meanValue;
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+ }
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+
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+ //梯度计算
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+ private double TTgrad(string a_strImgPath)
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+ {
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+ //读入Img文件
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+ if (!File.Exists(a_strImgPath))
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+ {
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+ return 0;
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+ }
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+
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+ Mat src;
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+ src = Cv2.ImRead(a_strImgPath);
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+
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+ src.CvtColor(ColorConversionCodes.BGR2GRAY);
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+
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+ Mat kernel = Cv2.GetStructuringElement(MorphShapes.Cross, new OpenCvSharp.Size(10, 10));
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+ Cv2.MorphologyEx(src, src, MorphTypes.Close, kernel);
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+
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+ Mat scalex = new Mat();
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+ Mat scaley = new Mat();
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+
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+ Cv2.Scharr(src, src, src.Depth(), 1, 0);
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+ Cv2.ConvertScaleAbs(src, scalex);
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+
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+ Cv2.Scharr(src, src, src.Depth(), 0, 1);
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+ Cv2.ConvertScaleAbs(src, scaley);
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+
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+ Cv2.AddWeighted(scalex, 0.5, scaley, 0.5, 0, src);
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+
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+ //图像的平均灰度
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+ double meanValue = 0.0;
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+ meanValue = Cv2.Mean(src)[0];
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+ return meanValue;
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+ }
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+
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+ //三选二算法
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+ private void ChooseBest(string a_strImgPath, out int a_nWd)
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+ {
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+ a_nWd = -1;
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+
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+ var files = Directory.GetFiles(a_strImgPath, "*.tif");
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+ float[] values = new float[files.Length];
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+
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+
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+ double smax1 = LoGMean(files[0]);
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+ int wdmax1 = int.Parse(System.IO.Path.GetFileNameWithoutExtension(files[0]));
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+
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+ double smax2 = Tenengrad(files[0]);
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+ int wdmax2 = wdmax1;
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+
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+ double smax3 = TTgrad(files[0]);
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+ int wdmax3 = wdmax1;
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+
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+
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+
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+ int x = 0;
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+ foreach (var file in files)
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+ {
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+
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+ int wd = int.Parse(System.IO.Path.GetFileNameWithoutExtension(file));
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+ double svalue1 = LoGMean(file);
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+ double svalue2 = Tenengrad(file);
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+ double svalue3 = TTgrad(file);
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+
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+
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+ if (smax1 < svalue1)
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+ {
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+ smax1 = svalue1;
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+ wdmax1 = wd;
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+ }
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+
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+ if (smax2 < svalue2)
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+ {
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+ smax2 = svalue2;
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+ wdmax2 = wd;
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+ }
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+
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+ if (smax3 < svalue3)
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+ {
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+ smax3 = svalue3;
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+ wdmax3 = wd;
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+ }
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+
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+ x++;
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+ }
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+
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+ SendMsg("LoG = " + wdmax1.ToString() + "，梯度 = " + wdmax2.ToString() + "，滤波 = " + wdmax3.ToString());
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+
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+
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+ if (wdmax1 == wdmax2 || wdmax1 == wdmax3)
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+ {
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+ a_nWd = wdmax1;
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+ SendMsg("焦距 = " + wdmax1.ToString());
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+ }
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+ else if (wdmax1 == wdmax2 || wdmax2 == wdmax3)
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+ {
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+ a_nWd = wdmax2;
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+ SendMsg("焦距 = " + wdmax2.ToString());
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+ }
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+ else if (wdmax3 == wdmax2 || wdmax1 == wdmax3)
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+ {
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+ a_nWd = wdmax3;
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+ SendMsg("焦距 = " + wdmax3.ToString());
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+ }
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+ else
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+ {
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+ SendMsg("对焦失败。");
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+ }
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+ }
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}
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}
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HaoShuang