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OpenCv案例(十三)：基于OpenCVSharp-模板匹之旋转角度匹配

作者：羊村懒王 | 2024-06-02 16:40:36

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opencvsharp

原模板匹配方法中，是无法进行任意角度和旋转匹配的，但我们在实际的使用中，模板图像的位置和方向都是不确定的，因此，就需要我们对模板图像进行预处理，处理后在进行模板匹配。

基本处理方法如下：

  • 模板图像读取
  • 进行模糊
  • 绘制轮廓
  • 形态学处理
  • 提取轮廓
  • 获取当前位置角度
  • 图像旋转。
  • 原图读取
  • 从4个角度进行模板匹配（0°，90°，180°，270°）
  • 记录每个角度的匹配值
  • 进行后续操作。

1：原图如下所示:

2：模板图像如下所示：

3：思路：在模板图像中，抠出图像，并且找到当前的旋转角度，将其恢复为正向0°，在进行对其模板匹配，给出匹配结果。处理过程图像如下：

分别是将其调整为正向后，0°，90°，180°，270°的旋转匹配，同时记录匹配度的值。

 

源码图下：

  1.  public List<Point2d> GetResult(Mat tempImage, string srcImgPath, out double robotRotateAngel, out double arcVal)
  2.  {
  3.      List<Point2d> point2Ds = new List<Point2d>();
  4.      robotRotateAngel = 999;
  5.      arcVal = 0;
  6.      try
  7.      {
  8.          double rotAngel;
  9.          Point2f centerPoint;
  10.          Rect rect;
  11.          Mat tempMat = SetTemplateImage1(tempImage, out rotAngel, out rect, out centerPoint);
  12.          bool matchRet = GetMatchRet1(srcImgPath, tempMat, rotAngel, out robotRotateAngel, out arcVal);
  13.  
  14.          if (!matchRet)
  15.          {
  16.              //图像识别失败
  17.              return null;
  18.          }
  19.      }
  20.      catch (Exception ex)
  21.      {
  22.          
  23.      }
  24.      return point2Ds;
  25.  }
  26.  
  27. public Mat SetTemplateImage1(Mat image, out double rotAngel, out Rect rect, out Point2f centerPoint)
  28. {
  29.     rotAngel = -1;
  30.     rect = new Rect();
  31.     centerPoint = new Point2f();
  32.     Mat blurImg = GaussBlurImage(image);//ip.MedBlurImage(image);// 
  33.     Mat cannyImg = new Mat();
  34.     Cv2.Canny(blurImg, cannyImg, 30, 90);
  35.     Mat morphImg = MorphImage(cannyImg);
  36.     //Cv2.ImShow("morphImg1", morphImg);
  37.     Mat roiImage = GetRioOutline(morphImg, image, out rotAngel, out rect, out centerPoint);
  38.     //Cv2.ImShow("roiImage", roiImage);
  39.     Mat rotImg = ImageRotate(roiImage, rotAngel, rect);
  40.     //Cv2.ImShow("rotImg", rotImg);
  41.     Mat mat = GetRoi(rotImg, rect);
  42.     Cv2.ImShow("mat", mat);
  43.     return mat;
  44. }
  45.  
  46.         /// <summary>
  47.         /// 高斯 模糊
  48.         /// </summary>
  49.         /// <param name="img"></param>
  50.         /// <returns></returns>
  51.         public Mat GaussBlurImage(Mat image)
  52.         {
  53.             Mat gaussianimage = new Mat();
  54.             Cv2.GaussianBlur(image, gaussianimage, new OpenCvSharp.Size(3, 3), 3, 3);//尽可能多的去除杂质
  55.             return gaussianimage;
  56.         }
  57.  
  58.         /// <summary>
  59.         /// 图像形态学操作
  60.         /// </summary>
  61.         /// <param name="image"></param>
  62.         /// <returns></returns>
  63.         public Mat MorphImage(Mat image)
  64.         {
  65.             Mat morphImage = new Mat();
  66.             Mat kernel = Cv2.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(3, 3), new Point(-1, -1));
  67.             Cv2.MorphologyEx(image, morphImage, MorphTypes.Gradient, kernel, new Point(-1, -1), 2);
  68.             return morphImage;
  69.         }
  70.  
  71.         /// <summary>
  72.         /// 提取图像轮廓
  73.         /// </summary>
  74.         /// <param name="morphImage">形态学图片</param>
  75.         /// <param name="srcImage">原图</param>
  76.         /// <param name="rotateAngel">返回旋转角度</param>
  77.         /// <param name="rect">返回获取的矩形边框</param>
  78.         /// <returns></returns>
  79.         public Mat GetRioOutline(Mat morphImage, Mat srcImage, out double rotateAngel, out Rect rect, out Point2f minRectcenterPoint)
  80.         {
  81.             OpenCvSharp.Point[][] contours;
  82.             HierarchyIndex[] hierarchies;
  83.             //Cv2.ImShow(",mmmm", morphImage);
  84.             Cv2.FindContours(morphImage, out contours, out hierarchies, RetrievalModes.External, ContourApproximationModes.ApproxTC89KCOS, new Point());
  85.             Mat connImg = Mat.Zeros(morphImage.Size(), MatType.CV_8UC3);
  86.             rotateAngel = 0;
  87.             //Point2f[] vertices = new Point2f[4];
  88.             minRectcenterPoint = new Point2f();
  89.             rect = new Rect();
  90.             int index = 0;
  91.             int count = -1;
  92.             //寻找最大轮廓
  93.             for (int i = 0; i < contours.Length; i++)
  94.             {
  95.                 for (int j = 0; j < contours[i].Length; j++)
  96.                 {
  97.                     if (count < contours[i].Length)
  98.                     {
  99.                         count = contours[i].Length;
  100.                         index = i;
  101.                     }
  102.                 }
  103.             }
  104.             //获取轮廓点的矩形区域
  105.             rect = Cv2.BoundingRect(contours[index]);
  106.             //minAreaRect():以X轴正方形为起点，顺时针为正，逆时针为负
  107.             //绘制Rio区域最小矩形
  108.             #region 绘制Rio区域最小矩形
  109.             RotatedRect minRect = Cv2.MinAreaRect(contours[index]);
  110.             rotateAngel = minRect.Angle;
  111.             minRectcenterPoint = minRect.Center;
  112.             //vertices = minRect.Points(); 
  113.             #endregion
  114.             //绘制最小矩形
  115.             #region 绘制最小矩形
  116.             //Cv2.Line(srcImage, Convert.ToInt32(vertices[0].X), Convert.ToInt32(vertices[0].Y), Convert.ToInt32(vertices[1].X), Convert.ToInt32(vertices[1].Y), new Scalar(0, 255, 255));
  117.             //Cv2.Line(srcImage, Convert.ToInt32(vertices[0].X), Convert.ToInt32(vertices[0].Y), Convert.ToInt32(vertices[3].X), Convert.ToInt32(vertices[3].Y), new Scalar(0, 255, 255));
  118.             //Cv2.Line(srcImage, Convert.ToInt32(vertices[1].X), Convert.ToInt32(vertices[1].Y), Convert.ToInt32(vertices[2].X), Convert.ToInt32(vertices[2].Y), new Scalar(0, 255, 255));
  119.             //Cv2.Line(srcImage, Convert.ToInt32(vertices[2].X), Convert.ToInt32(vertices[2].Y), Convert.ToInt32(vertices[3].X), Convert.ToInt32(vertices[3].Y), new Scalar(0, 255, 255));
  120.             //Console.WriteLine("AngleRect_angle: {0}", minRect.Angle); 
  121.             #endregion
  122.  
  123.             //Cv2.ImShow("srcImage", srcImage);
  124.  
  125.             return srcImage;
  126.         }
  127.  
  128.         /// <summary>
  129.         /// 图像旋转
  130.         /// </summary>
  131.         /// <param name="image">旋转图像</param>
  132.         /// <param name="rotateAngel">旋转角度</param>
  133.         /// <returns></returns>
  134.         public Mat ImageRotate(Mat image, double rotateAngel, Rect rect)
  135.         {
  136.             if (rotateAngel > -90 && rotateAngel <= -45)
  137.             {
  138.                 rotateAngel += 90;
  139.             }
  140.             else if (!(rotateAngel > -45 && rotateAngel < 0))
  141.             {
  142.                 //degree = degree;
  143.                 rotateAngel = 0;
  144.             }
  145.             //OpenCvSharp.Point center = new OpenCvSharp.Point(image.Cols / 2, image.Rows / 2);
  146.             //以被截取的区域中心位置旋转
  147.             //边缘放大截取
  148.             OpenCvSharp.Point center = new OpenCvSharp.Point(rect.TopLeft.X + (rect.Width / 2), rect.TopLeft.Y + (rect.Height / 2));
  149.             //截取最小矩形
  150.             //OpenCvSharp.Point center = new OpenCvSharp.Point(image.Cols / 2, image.Rows / 2);
  151.             double angle = rotateAngel;
  152.             double scale = 1;
  153.             Mat rotate = new Mat(2, 3, MatType.CV_32FC1);
  154.             rotate = Cv2.GetRotationMatrix2D(center, angle, scale);//getRotationMatrix2D():以X轴正方形为起点，顺时针为负，逆时针为正
  155.             Mat rotImage = new Mat();
  156.             Cv2.WarpAffine(image, rotImage, rotate, image.Size(), InterpolationFlags.Linear, BorderTypes.Wrap);
  157.             int winSize = 0;
  158.             if (image.Cols > image.Rows)
  159.             {
  160.                 winSize = image.Cols;
  161.             }
  162.             else
  163.             {
  164.                 winSize = image.Rows;
  165.             }
  166.             return rotImage;
  167.         }
  168.  
  169.  
  170.         /// <summary>
  171.         /// 获取感兴趣区域
  172.         /// </summary>
  173.         /// <param name="image">图像</param>
  174.         /// <param name="rect">面积</param>
  175.         /// <returns></returns>
  176.         public Mat GetRoi(Mat image, Rect rect)
  177.         {
  178.             //Mat imageRoi = new Mat(image, new Rect(new Point(rect.TopLeft.X - rect.Width / 2, rect.TopLeft.Y), new Size(rect.Height, rect.Height)));
  179.             Mat imageRoi = new Mat(image, new Rect(new Point(rect.TopLeft.X, rect.TopLeft.Y), new Size(rect.Width, rect.Height)));
  180.             return imageRoi;
  181.         }
  182.  
  183.         Dictionary<int, double> angelDic1;
  184.         /// <summary>
  185.         /// 模板匹配是否成功
  186.         /// </summary>
  187.         /// <param name="srcBmp">原图</param>
  188.         /// <param name="templateMat">模板图像</param>
  189.         /// <param name="rotAngel">初始旋转角度</param>
  190.         /// <param name="robotRotateAngel">机器人需要旋转的角度</param>
  191.         /// <returns></returns>
  192.         public bool GetMatchRet1(string srcImgFilePath, Mat templateMat, double rotAngel, out double robotRotateAngel, out double arcValue)
  193.         {
  194.             double matchVal = 0;
  195.             //最大旋转角度360
  196.             robotRotateAngel = 999;
  197.             arcValue = 0;
  198.             try
  199.             {
  200.                 Mat src = Cv2.ImRead(@"E:\SoftwarePackage\CodePackage\ImgPro\Img\T1.bmp");
  201.                 //src.ConvertTo(src, MatType.CV_8UC4);
  202.                 if (src.Empty())
  203.                 {
  204.                     //Console.WriteLine("src could not load image...\n");
  205.                     return false;
  206.                 }
  207.                 Cv2.ImShow("src", src);
  208.                 //Mat templateMat = Cv2.ImRead(@"E:\SoftwarePackage\CodePackage\ImgPro\Img\T21.bmp");
  209.                 if (templateMat.Empty())
  210.                 {
  211.                     //Console.WriteLine("src could not load image...\n");
  212.                     return false;
  213.                 }
  214.  
  215.                 angelDic1 = new Dictionary<int, double>(); ;
  216.                 //记录角度
  217.                 int rotateAngel = 0;
  218.                 //第一张调正之后的图像
  219.                 //Cv2.ImShow(0.ToString(), mat);
  220.                 Point p;
  221.                 Bitmap rotateBmp;
  222.                 //旋转图像4个角度
  223.                 for (int i = 0; i < 4; i++)
  224.                 {
  225.                     if (templateMat.Rows > src.Rows || templateMat.Cols > src.Cols)
  226.                     {
  227.                         continue;
  228.                     }
  229.                     Bitmap bmp = MatchTemplate(templateMat, src, out p, out matchVal);
  230.                     if (matchVal > TemplateMatchThreshold)
  231.                     {
  232.                         angelDic1.Add(rotateAngel, matchVal);
  233.                     }
  234.                     //Mat rotImg1 = ip.ImageRotate(mat, 90);
  235.                     rotateBmp = BitmapConverter.ToBitmap(templateMat);
  236.                     rotateBmp.RotateFlip(RotateFlipType.Rotate90FlipXY);
  237.                     rotateAngel += 90;
  238.                     templateMat = BitmapConverter.ToMat(rotateBmp);
  239.                     if (1 + i > 3)
  240.                     {
  241.                         break;
  242.                     }
  243.                     Cv2.ImShow((i + 1).ToString(), templateMat);
  244.                 }
  245.                 //若匹配值没有符合条件
  246.                 if (angelDic1.Count < 1)
  247.                 {
  248.                     return false;
  249.                 }
  250.  
  251.                 List<double> matchRet = new List<double>();
  252.                 foreach (KeyValuePair<int, double> kvp in angelDic1)
  253.                 {
  254.                     matchRet.Add(kvp.Value);
  255.                 }
  256.                 //判断匹配最大值是否大于设定阈值 否则 匹配失败
  257.                 //if (matchRet.Max() < TemplateMatchThreshold)
  258.                 //{
  259.                 //    return false;
  260.                 //}
  261.                 //抠出模板图像 与原图进行模板匹配,并且记住最大匹配度的角度
  262.                 var ag = angelDic1.Where(q => q.Value == matchRet.Max()).Select(q => q.Key);
  263.                 robotRotateAngel = CalcRotateAngel(rotAngel, ag.Max());
  264.                 //角度转弧度
  265.                 arcValue = robotRotateAngel * arc;
  266.             }
  267.             catch (Exception ex)
  268.             {
  269.                 //LogHelper.WriteLog(ex.Message, ex);
  270.             }
  271.             return true;
  272.         }
  273.  
  274.         private double arc1 = Math.PI / 180;
  275.  
  276.         /// <summary>
  277.         /// 模板匹配
  278.         /// </summary>
  279.         /// <param name="tempalte">模板图片像</param>
  280.         /// <param name="srcPic">被匹配图像</param>
  281.         /// <returns>标注匹配区域的图像</returns>
  282.         public Bitmap MatchTemplate(Mat tempalte, Mat srcPic, out OpenCvSharp.Point tempPoint, out double matchValue)
  283.         {
  284.  
  285.             using (Mat result = new Mat()) //匹配结果
  286.             {                             //模板匹配
  287.                 Double minVul;
  288.                 Double maxVul;
  289.                 OpenCvSharp.Point minLoc = new OpenCvSharp.Point(0, 0);
  290.                 OpenCvSharp.Point maxLoc = new OpenCvSharp.Point(0, 0);
  291.                 OpenCvSharp.Point matchLoc = new OpenCvSharp.Point(0, 0);
  292.                 Cv2.MatchTemplate(srcPic, tempalte, result, TemplateMatchModes.CCoeffNormed);//CCoeffNormed  最好匹配为1,值越小匹配越差 xxxNormed的算法无需归一化
  293.                                                                                              //Cv2.Normalize(result, result, 0, 1, NormTypes.MinMax, -1);//归一化
  294.                 Cv2.MinMaxLoc(result, out minVul, out maxVul, out minLoc, out maxLoc);//查找极值
  295.                                                                                       //Cv2.MinMaxLoc(result, out minVul, out maxVul, out minLoc, out maxLoc, null);//查找极值
  296.                 matchLoc = maxLoc;//最大值坐标
  297.                                   //result.Set(matchLoc.Y, matchLoc.X, 0);//改变最大值为最小值  
  298.                 Mat mask = srcPic.Clone();//复制整个矩阵
  299.                                           //Console.WriteLine("最大值：{0}，X:{1}，Y:{2}", maxVul, matchLoc.Y, matchLoc.X);
  300.                 matchValue = maxVul;
  301.                 tempPoint.X = matchLoc.X;
  302.                 tempPoint.Y = matchLoc.Y;
  303.                 //画框显示 :对角线画框，起点和终点，都用Point，线宽
  304.                 if (matchValue > TemplateMatchThreshold)
  305.                 {
  306.                     Cv2.Rectangle(mask, matchLoc, new OpenCvSharp.Point(matchLoc.X + tempalte.Cols, matchLoc.Y + tempalte.Rows), Scalar.Green, 2);//2代表画的线条的宽细程度
  307.                 }
  308.                 return OpenCvSharp.Extensions.BitmapConverter.ToBitmap(mask);
  309.             }
  310.         }
  311.  
  312.         /// <summary>
  313.         /// 计算角度
  314.         /// </summary>
  315.         /// <param name="srcAngel"></param>
  316.         /// <param name="rotateAngle"></param>
  317.         /// <returns></returns>
  318.         public double CalcRotateAngel(double srcAngel, int rotateAngle)
  319.         {
  320.             //逆时针旋转为负 顺时针旋转为正
  321.             double tempSrcAngel = Math.Abs(srcAngel);
  322.             double resultAngel = -1;
  323.             if (tempSrcAngel >= 45)
  324.             {
  325.                 switch (rotateAngle)
  326.                 {
  327.                     case 0:
  328.                         resultAngel = 90 - tempSrcAngel;
  329.                         break;
  330.                     case 90:
  331.                         resultAngel = 180 - tempSrcAngel;
  332.                         break;
  333.                     case 180:
  334.                         //逆时针
  335.                         resultAngel = -(90 + tempSrcAngel);
  336.                         break;
  337.                     case 270:
  338.                         //逆时针
  339.                         resultAngel = -tempSrcAngel;
  340.                         break;
  341.                 }
  342.             }
  343.             else if (tempSrcAngel < 45)
  344.             {
  345.                 switch (rotateAngle)
  346.                 {
  347.                     case 0:
  348.                         //逆时针
  349.                         resultAngel = -tempSrcAngel;
  350.                         break;
  351.                     case 90:
  352.                         resultAngel = 90 - tempSrcAngel;
  353.                         break;
  354.                     case 180:
  355.                         resultAngel = 90 + tempSrcAngel;
  356.                         break;
  357.                     case 270:
  358.                         //逆时针
  359.                         resultAngel = -(90 + tempSrcAngel);
  360.                         break;
  361.                 }
  362.             }
  363.             return resultAngel;
  364.         }

完整代码都在上面了，感兴趣的小伙伴可以在优化优化。下个案例见。

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