获取元件面积时使用直方图二值化

AccImage/ImageUtil.cs

@@ -211,13 +211,13 @@ namespace Acc.Img
             Cv2.CvtColor(grayMat, grayMat, ColorConversionCodes.RGB2GRAY);
             CvBlobs blobs = AutoThreshBlobs(ref grayMat, itemArea);
             int totalCount = findCircles(ref imageMat, grayMat, blobs, itemArea);
-            
+
             //int totalCount = CountBlobs(blobs, itemArea, ref imageMat);
             image = BitmapConverter.ToBitmap(imageMat);
             return totalCount;
         }
 
-        
+
         private static void FindCours(Mat srcMat, Mat threshMat)
         {
             Mat[] contours = null;
@@ -251,9 +251,6 @@ namespace Acc.Img
             }
         }
 
-
-
-
         private static void LabelBlobsInCircle(ref string[] labels, List<CvBlob> blobList, double centerX, double centerY, double radius)
         {
             int labelCount = 0;
@@ -381,10 +378,14 @@ namespace Acc.Img
             }
             return Math.Sqrt(avgArea);
         }
-        
 
-        private static CvBlobs AutoThreshBlobs(ref Mat imageMat, int blobArea)
+        private static CvBlobs AutoThreshBlobs(ref Mat imageMat, int blobArea = -1)
         {
+            if (blobArea == -1)
+            {
+                //获取元器件特征时，假定的blob面积
+                blobArea = 3;
+            }
             Mat[] mats = new Mat[] { imageMat };//一张图片，初始化为panda
             Mat hist = new Mat();//用来接收直方图
             int[] channels = new int[] { 0 };//一个通道,初始化为通道0
@@ -406,7 +407,7 @@ namespace Acc.Img
             for (int i = 0; i < 256; i++)//直方图
             {
                 double len = hist.Get<double>(i);
-                if(len > 100)
+                if (len > 100)
                 {//灰度值的像素数小于100的忽略
                     percent = percent + len / total;
                     if (startIndex == -1)
@@ -422,56 +423,37 @@ namespace Acc.Img
                 }
             }
 
-            int avgIndex = (startIndex + endIndex) / 2;
+            //int avgIndex = (startIndex + endIndex) / 2;
+            //Mat threshMat = new Mat();
+            //Cv2.Threshold(imageMat, threshMat, avgIndex, 255, ThresholdTypes.BinaryInv);
+            //CvBlobs resultBlobs = new CvBlobs();
+            //resultBlobs.Label(threshMat);
+            //List<CvBlob> autoBlobList = resultBlobs.Values.Where(b => b.Area > blobArea).ToList();
+            //int blobCount = resultBlobs.Count();
             Mat threshMat = new Mat();
-            Cv2.Threshold(imageMat, threshMat, avgIndex, 255, ThresholdTypes.BinaryInv);
+            int blobCount = 0;
             CvBlobs resultBlobs = new CvBlobs();
-            resultBlobs.Label(threshMat);
-            List<CvBlob> autoBlobList = resultBlobs.Values.Where(b => b.Area > blobArea).ToList();
-            int blobCount = resultBlobs.Count();
-            int threshIndex = avgIndex;
+            int threshIndex = (startIndex + endIndex) / 2;
             double theArea = blobArea * 0.8;
             if (theArea < 1) theArea = 1;
-            
-            while (true)
-            {
-                //阈值向下走，找满足条件Blob数量最多的
-                threshIndex = threshIndex - 1;
-                Cv2.Threshold(imageMat, threshMat, threshIndex, 255, ThresholdTypes.BinaryInv);
-                CvBlobs blobs = new CvBlobs();
-                blobs.Label(threshMat);
-                List<CvBlob> blobList = blobs.Values.Where(b => b.Area > theArea).ToList();
-                if (blobList.Count > blobCount)
-                {
-                    resultBlobs = blobs;
-                    blobCount = blobList.Count;
-                }
-                else
-                {
-                    break;
-                }
-            }
-            threshIndex = avgIndex;
-            while (true)
+            Console.WriteLine("Avg Thresh: " + threshIndex);
+            for (int index = startIndex; index < endIndex; index++)
             {
-                //阈值向上走，找满足条件Blob数量最多的
-                threshIndex = threshIndex + 1;
-                Cv2.Threshold(imageMat, threshMat, threshIndex, 255, ThresholdTypes.BinaryInv);
+                Mat tempThreshMat = new Mat();
+                Cv2.Threshold(imageMat, tempThreshMat, threshIndex, 255, ThresholdTypes.BinaryInv);
                 CvBlobs blobs = new CvBlobs();
-                blobs.Label(threshMat);
+                blobs.Label(tempThreshMat);
                 List<CvBlob> blobList = blobs.Values.Where(b => b.Area > theArea).ToList();
                 if (blobList.Count > blobCount)
                 {
+                    threshMat = tempThreshMat;
+                    threshIndex = index;
                     resultBlobs = blobs;
                     blobCount = blobList.Count;
                 }
-                else
-                {
-                    break;
-                }
             }
             imageMat = threshMat;
-            Console.WriteLine(threshIndex + "==== Blob: " + blobCount + "  Area:" + theArea);
+            Console.WriteLine("result thresh: " +  threshIndex + "==== Blob: " + blobCount + "  Area:" + theArea);
             return resultBlobs;
         }
 
@@ -1055,12 +1037,16 @@ namespace Acc.Img
             Mat dst = new Mat();
             Cv2.CvtColor(imageMat, dst, ColorConversionCodes.RGB2GRAY);
             //全局二值化
-            Cv2.Threshold(dst, dst, 0, 255, ThresholdTypes.Otsu | ThresholdTypes.BinaryInv);
+            //Cv2.Threshold(dst, dst, 0, 255, ThresholdTypes.Otsu | ThresholdTypes.BinaryInv);
+            //image = BitmapConverter.ToBitmap(dst);
+            //CvBlobs blobs = new CvBlobs();
+            //blobs.Label(dst);
+            
+            CvBlobs blobs = AutoThreshBlobs(ref dst);
             image = BitmapConverter.ToBitmap(dst);
-            CvBlobs blobs = new CvBlobs();
-            blobs.Label(dst);
+
             int blobArea = -1;
-            foreach(CvBlob blob in blobs.Values) {
+            foreach (CvBlob blob in blobs.Values) {
                 if (blob.Rect.Contains(new OpenCvSharp.Point(markX, markY)))
                 {
                     if (blob.Area < blobArea || blobArea == -1)

AccImage/SplitItem.cs

@@ -31,7 +31,7 @@ namespace AccImage
             {
                 //与平均半径差值在10%以内，认为OK
                 double diff = avgRadius - currentMaxRadius;
-                if (diff/avgRadius <= 0.4)
+                if (diff/avgRadius <= 0.5)
                 {
                     isValid = true;
                 }