Automatic calculation of low and high thresholds for the Canny operation in opencv

Question

In openCV, the low and high thresholds for the canny operator are mandatory:

cvCanny(input,output,thresh1,thresh2)

In Matlab, there\'s an o

Answer 1

I have looked through the source code of Matlab Canny edge detection and I managed to write it in Java with OpenCV 3.

private static Mat getpartialedge(Mat image){
    double nonEdgeRate = 0.6;
    double thresholdRate = 0.6;
    double w = image.cols();
    double h = image.rows();
    int bins = 256;
    Mat sobel = new Mat();
    Mat sobelx = new Mat();
    Mat sobely = new Mat();
    Mat sobelxabs = new Mat();
    Mat sobelyabs = new Mat(); 
    Size gsz = new Size(5, 5);
    if(false) {
        Imgproc.Canny(image, sobel, 41, 71);
    }else {

        //Imgproc.GaussianBlur(graycopy,graycopy, gsz, 2);
        //Imgproc.dilate(image, image, kernel8);
        Imgproc.GaussianBlur(image, image, gsz, 2);


        int apertureSize = 3;
        Imgproc.Sobel(image, sobelx, CvType.CV_16S, 1, 0, apertureSize, 1, 0);
        Core.convertScaleAbs(sobelx, sobelxabs);
        Imgproc.Sobel(image, sobely, CvType.CV_16S, 0, 1, apertureSize, 1, 0);
        Core.convertScaleAbs(sobely, sobelyabs);
        Core.addWeighted(sobelxabs, 1, sobelyabs, 1, 0, sobel);
        sobel.convertTo(sobel, CvType.CV_8U);


        Mat equalized = new Mat();
        Imgproc.equalizeHist(sobel, equalized);
        Imgcodecs.imwrite(filePath + "aftersobel(eq).png", equalized);
        Imgcodecs.imwrite(filePath + "aftersobel.png", sobel);


        Mat hist = new Mat();
        List matList = new ArrayList();
        matList.add(sobel);
        Imgproc.calcHist(matList, new MatOfInt(0), new Mat(), hist, new MatOfInt(bins), new MatOfFloat(0f, 256f));
        float accu = 0;
        float t = (float) (nonEdgeRate * w * h);
        float bon = 0;
        float[] accutemp = new float[bins];
        for (int i = 0; i < bins; i++) {
            float tf[] = new float[1];
            hist.get(i, 0, tf);
            accu = accu + tf[0];
            accutemp[i] = accu;
            if (accu > t) {
                bon = (float) i;
                break;
            }
        }
        Imgproc.threshold(sobel, sobel, bon, 255, Imgproc.THRESH_BINARY);
        double ut = bon;
        double lt = thresholdRate * bon;


        Imgproc.Canny(image, sobel, lt, ut);
        //Imgproc.dilate(sobel, sobel, kernel2);
    }
    return sobel;
}

The filepath is the place to hold the output images. And the input image should be a gray-scale image with U8 data type. The basic principle is to rule out nonEdgeRate(60%) pixel as non-edge pixel by the brightness. A histogram is used to sort the brightness and the upper threshold will be set so that there are 60% pixels below it. The lower threshold is set by multiplying the upper threshold by the thresholdRate(0.6).

Note that the double nonEdgeRate = 0.6 and double thresholdRate = 0.6 is tuned by myself in my specific use case. Th original values are 0.7 and 0.4 separately in matlab.