visual-studio - HoughCircles 在 OpenCV 中无法正确检测圆圈

Question

我使用的是 Visual Studio 2015、OpenCV.3 和 EmguCV.3。
我的代码如下所示，结果如图所示。我知道问题是HoughCircles函数的输入值，但不知道哪些输入适合这张图片。我很感激任何帮助。

                Image<Gray, byte> OriginalImage = new Image<Gray, byte>(Openfile.FileName);
                Image<Gray, byte> ResizedImage = OriginalImage.Resize(OriginalImage.Width / 2, OriginalImage.Height / 2, Emgu.CV.CvEnum.Inter.Cubic);

                //********** Convert Image to Binary
                Image<Gray, byte> smoothImg = 
                ResizedImage.SmoothGaussian(5);
                smoothImg._Erode(5);
                smoothImg._Dilate(5);
                Image<Gray, byte> BinaryImage = 
                smoothImg.ThresholdBinary(new Gray(20), new Gray(255));

                //********** Find Circles
                Image<Rgb, byte> ROIImgScaledCircles = ROIImgScaled.Convert<Rgb, byte>();
                CircleF[] circles = smoothImg.HoughCircles(
                    new Gray(180),//cannyThreshold
                    new Gray(60),//circleAccumulatorThreshold
                    2.0, //dp:Resolution of the accumulator used to detect centers of the circles
                    10.0, //min distance 
                    10, //min radius
                    128 //max radius
                    )[0]; //Get the circles from the first channel
                foreach (CircleF cir in circles)
                {
                    ROIImgScaledCircles.Draw(cir, new Rgb(235, 20, 30), 1);
                }                   
                pbxCircles.Image = ROIImgScaledCircles.ToBitmap();

原图:



成立圈子:

Answer 1

使用完整的形状，您可能会发现检测边缘然后找到轮廓更容易。下面是一个例子:

    Image<Bgr, byte> original = new Image<Bgr, byte>(@"E:\Downloads\original.jpg");
    UMat grayscale = new UMat();            
    UMat pyrdown = new UMat();
    UMat canny = new UMat();

    double cannyThreshold = 128;

    CvInvoke.CvtColor(original, grayscale, ColorConversion.Bgr2Gray);        
    // remove noise and run edge detection
    CvInvoke.PyrDown(grayscale, pyrdown);
    CvInvoke.PyrUp(pyrdown, grayscale);
    CvInvoke.Canny(grayscale, canny, cannyThreshold, cannyThreshold * 2);

    Image<Bgr, byte> result = original.Copy();
    // find and draw circles   
    VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
    CvInvoke.FindContours(canny, contours, null, RetrType.List, ChainApproxMethod.ChainApproxSimple);
    //CvInvoke.DrawContours(result, contours, -1, new MCvScalar(0, 0, 255));
    for (int i = 0; i < contours.Size; i++)
    {
        Ellipse ellipse = new Ellipse(CvInvoke.FitEllipse(contours[i]));
        result.Draw(ellipse, new Bgr(Color.Red), 1);
    }

    result.Save(@"E:\Downloads\circles.jpg");

结果如下，从左到右:

原图

模糊的图像(使用 pyrdown/pyrup)

精明边缘检测的结果

从轮廓重建圆