使用matchTemplate方法，输出图像将为您提供像素值，表示模板在此特定位置的匹配程度。 在您的情况下，由于您使用了MatchTemplateMethod.SqDiff，因此值越低，匹配越好。

问题是，当你使用minMaxLoc函数时，你会得到你要求的东西，这是最好的匹配，在这种情况下，min）。

所有匹配都是其值低于您设置的阈值的像素。 既然我不习惯csharp，这就是它在C ++中的用法，你可以进行翻译：

 // after your call to MatchTemplate float threshold = 0.08; cv::Mat thresholdedImage; cv::threshold(result, thresholdedImage, threshold, 255, CV_THRESH_BINARY); // the above will set pixels to 0 in thresholdedImage if their value in result is lower than the threshold, to 255 if it is larger. // in C++ it could also be written cv::Mat thresholdedImage = result < threshold; // Now loop over pixels of thresholdedImage, and draw your matches for (int r = 0; r < thresholdedImage.rows; ++r) { for (int c = 0; c < thresholdedImage.cols; ++c) { if (!thresholdedImage.at(r, c)) // = thresholdedImage(r,c) == 0 cv::circle(sourceColor, cv::Point(c, r), template.cols/2, CV_RGB(0,255,0), 1); } } 

从C ++翻译并使用OpenCvSharp包装器，上面的代码替换了minMaxLoc行，对我有用：

 double threshold=0.9 var thresholdImage=Cv.CreateImage(newImageSize, BitDepth.F32,1); Cv.Threshold(result, thresholdImage, threshold, 255, ThresholdType.Binary); for (int r = 0; r < thresholdImage.GetSize().Height; r++) { for (int c = 0; c < thresholdImage.GetSize().Width; c++) { if (thresholdImage.GetRow(r)[c].Val0 > 0) { Cv.Rectangle(soruceColour, Cv.Point(c, r), Cv.Point(c + template.Width, r + template.Height), CvColor.Red, 1, 0, 0); } } } 

这是使用Min_Max和Match_Template方法的解决方案。 希望它会有所帮助。

  public void multipleTemplateMatch(string SourceImages, string tempImage) { Image image_source = new Image(SourceImages); Image image_partial1 = new Image(tempImage); double threshold = 0.9; ImageFinder imageFinder = new ImageFinder(image_source, image_partial1, threshold); imageFinder.FindThenShow(); } 

这是一个有用的课程。

 class ImageFinder { private List rectangles; public Image BaseImage { get; set; } public Image SubImage { get; set; } public Image ResultImage { get; set; } public double Threashold { get; set; } public List Rectangles { get { return rectangles; } } public ImageFinder(Image baseImage, Image subImage, double threashold) { rectangles = new List(); BaseImage = baseImage; SubImage = subImage; Threashold = threashold; } public void FindThenShow() { FindImage(); DrawRectanglesOnImage(); ShowImage(); } public void DrawRectanglesOnImage() { ResultImage = BaseImage.Copy(); foreach (var rectangle in this.rectangles) { ResultImage.Draw(rectangle, new Bgr(Color.Blue), 1); } } public void FindImage() { rectangles = new List(); using (Image imgSrc = BaseImage.Copy()) { while (true) { using (Image result = imgSrc.MatchTemplate(SubImage, TemplateMatchingType.CcoeffNormed)) { double[] minValues, maxValues; Point[] minLocations, maxLocations; result.MinMax(out minValues, out maxValues, out minLocations, out maxLocations); if (maxValues[0] > Threashold) { Rectangle match = new Rectangle(maxLocations[0], SubImage.Size); imgSrc.Draw(match, new Bgr(Color.Blue), -1); rectangles.Add(match); } else { break; } } } } } public void ShowImage() { Random rNo = new Random(); string outFilename = "matched Templates" + rNo.Next(); CvInvoke.Imshow(outFilename, ResultImage); } } 

如果您觉得这很有用，请投票同样有用。 谢谢

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