C#-OpenCvSharp查找遍历轮廓范围内的点

private Mat GoFindContours(Mat mat, string name, out Mat[] countoursMat)
{
    countoursMat = null;
    Mat useLessMat = new Mat();
    Mat Gray;
    Mat Bgr;
    Mat binary = new Mat();
    Mat NoNiosePointMat = new Mat();
    if (!mat.GetGrayAndBgr(out Gray, out Bgr)) return null;
    //在背景中提取亮目标，TRIANGLE法优于OTSU法，而在亮背景中提取暗目标，OTSU法优于TRIANGLE法
    //Cv2.Threshold(Gray, binary, Parameters.ThreshVal, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);
    Cv2.Threshold(Gray, binary, Parameters.ThreshVal, 255, ThresholdTypes.Binary);
    //当binary二值化图像存在噪点时，使用中值滤波去除噪点，使其更好的查找和绘制轮廓
    Cv2.MedianBlur(binary, NoNiosePointMat, Parameters.KernelSize);
    //腐蚀，查找精度更高的轮廓
    InputArray kernel = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3), new Point(-1, -1));
    Cv2.Erode(NoNiosePointMat, NoNiosePointMat, kernel);
    //获取Mat类型的轮廓，以便后续查找点位是否在轮廓上
    Cv2.FindContours(NoNiosePointMat, out countoursMat, useLessMat, (RetrievalModes)Enum.Parse(typeof(RetrievalModes), Parameters.SelectRetrievalModes), ContourApproximationModes.ApproxNone);
    ContourList[name] = contours.OrderBy(p => p.Length).ToArray();
    //获取轮廓内所有的点
    var isFind = NoNiosePointMat.FindNonZero().GetArray(out Point[] points);
    //是一个闭合图像，有两条闭合轮廓
    Parallel.ForEach(points, new ParallelOptions { MaxDegreeOfParallelism = Environment.ProcessorCount }, (p, loopState) =>
    {
        //是否返回距离值，如果是false，1表示在内面，0表示在边界上，-1表示在外部，true返回实际距离
        if (Cv2.PointPolygonTest(countoursMat[0], p, false) != 0 && Cv2.PointPolygonTest(countoursMat[1], p, false) != 0)
        {
        }
     })
    return NoNiosePointMat;
}