Emgu-WPF学习使用-Rectangle识别

环境：Win8 64位 Vs2015

Emgu 版本：emgucv-windesktop 3.2.0.2682

示例图上部流程：原图->灰度化->截断阈值化->中值模糊->高斯模糊->膨胀->腐蚀->Ostu二值化。

// 灰度化
Image<Gray, byte> imgGray = new Image<Gray, byte>(imgSrc.Size);
CvInvoke.CvtColor(imgSrc, imgGray, ColorConversion.Bgr2Gray);

//截断阈值化
Image<Gray, byte> imgThresholdTrunc = new Image<Gray, byte>(imgGray.Size);
CvInvoke.Threshold(imgGray, imgThresholdTrunc, 60, 255, ThresholdType.Trunc);

// 中值模糊
Image<Gray, byte> imgMedian = imgThresholdTrunc.SmoothMedian(7); //使用5*5的卷积核

// 高斯模糊
Image<Gray, byte> imgGaussian = imgMedian.SmoothGaussian(5);
// 膨胀，消除杂点
Mat oMat2 = CvInvoke.GetStructuringElement(Emgu.CV.CvEnum.ElementShape.Rectangle,
    new System.Drawing.Size(5, 5), new System.Drawing.Point(0, 0));
Image<Gray, byte> imgErode = new Image<Gray, byte>(imgGray.Size);
CvInvoke.Erode(imgGaussian, imgErode, oMat2, new System.Drawing.Point(0, 0), 4,
    BorderType.Default, new MCvScalar(255, 0, 0, 255));

// 腐蚀，消除杂点
Image<Gray, byte> imgDilate = new Image<Gray, byte>(imgGray.Size);
CvInvoke.Dilate(imgErode, imgDilate, oMat2, new System.Drawing.Point(0, 0), 4,
    BorderType.Default, new MCvScalar(255, 0, 0, 255));

// Otsu二值化
Image<Gray, byte> imgThresholdOtsu = new Image<Gray, byte>(imgGray.Size);
CvInvoke.Threshold(imgDilate, imgThresholdOtsu, 0, 255, ThresholdType.Otsu);

示例图下部流程：原图->灰度化->截断阈值化->消除裂缝->Ostu二值化->识别Contours->绘制Contours.

// 灰度化
Image<Gray, byte> imgGray = new Image<Gray, byte>(imgSrc.Size);
CvInvoke.CvtColor(imgSrc, imgGray, ColorConversion.Bgr2Gray);

//截断阈值化
Image<Gray, byte> imgThresholdTrunc = new Image<Gray, byte>(imgGray.Size);
CvInvoke.Threshold(imgGray, imgThresholdTrunc, 60, 255, ThresholdType.Trunc);

// 消除裂缝
Mat oMat1 = CvInvoke.GetStructuringElement(Emgu.CV.CvEnum.ElementShape.Rectangle,
    new System.Drawing.Size(6, 6), new System.Drawing.Point(0, 0));
Image<Gray, byte> imgMorphologyEx = new Image<Gray, byte>(imgGray.Size);
CvInvoke.MorphologyEx(imgThresholdTrunc, imgMorphologyEx, Emgu.CV.CvEnum.MorphOp.Close, oMat1,
    new System.Drawing.Point(0, 0), 1, BorderType.Default,
    new MCvScalar(255, 0, 0, 255));

// Otsu二值化
Image<Gray, byte> imgThresholdOtsu = new Image<Gray, byte>(imgGray.Size);
CvInvoke.Threshold(imgMorphologyEx, imgThresholdOtsu, 0, 255, ThresholdType.Otsu);

List<RotatedRect> boxList = new List<RotatedRect>(); //a box is a rotated rectangle
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
CvInvoke.FindContours(imgThresholdOtsu, contours, null, RetrType.List,
    ChainApproxMethod.ChainApproxSimple);

Image<Bgr, byte> imgResult = new Image<Bgr, byte>(imgGray.Size);
CvInvoke.CvtColor(imgThresholdOtsu, imgResult, ColorConversion.Gray2Bgr);
MCvScalar oScaler = new MCvScalar(40, 255, 255, 255);
int count = contours.Size;
for (int i = 0; i < count; i++)
{
    using (VectorOfPoint contour = contours[i])
    using (VectorOfPoint approxContour = new VectorOfPoint())
    {
        CvInvoke.ApproxPolyDP(contour, approxContour, CvInvoke.ArcLength(contour, true) * 0.05, true);
        double dArea = CvInvoke.ContourArea(approxContour, false);
        if (dArea > imgThresholdOtsu.Rows * imgThresholdOtsu.Cols / 3d)
        {
            if (approxContour.Size == 4)
            {
                #region determine if all the angles in the contour are within [80, 100] degree
                bool isRectangle = true;
                System.Drawing.Point[] pts = approxContour.ToArray();
                LineSegment2D[] edges = Emgu.CV.PointCollection.PolyLine(pts, true);

                for (int j = 0; j < edges.Length; j++)
                {
                    double angle = Math.Abs(
                        edges[(j + 1) % edges.Length].GetExteriorAngleDegree(edges[j]));
                    if (angle < 80 || angle > 100)
                    {
                        isRectangle = false;
                        break;
                    }
                }
                #endregion

                if (isRectangle)
                    CvInvoke.DrawContours(imgResult, contours, i, oScaler, 3);
            }
        }
    }
}