Issues implementing skeletonize algorithm in opencv

Question

I am trying to implement skeletonize alogrithm using opencv. I want to reduce the number of pixels of the below image and make it thin.

Here is the image which I want to skeletonize:

Here is my code:

Mat image = imread("4X4_b9.png",IMREAD_GRAYSCALE);
    int rows = image.rows;
    int cols = image.cols;
    int size = rows * cols;
    Mat skel = Mat::zeros(image.rows,image.cols,CV_8U);
    threshold(image, image, 100, 255, THRESH_BINARY);
    Mat element = getStructuringElement(MORPH_CROSS, Size(3,3));
    bool done = false;
    while(done == false){
        Mat eroded;
        erode(image, eroded, element);
        Mat temp;
        dilate(eroded, temp, element);
        subtract(image, temp, temp);
        bitwise_or(skel, temp, skel);
        eroded.copyTo(image);

        int zeros = size - countNonZero(image);
        if(zeros == size){
            done = true;
        }
    }

    imshow("skel",skel);
    waitKey(0);
    destroyAllWindows();

Note: I tried this link for reference: python implemented

After running this lot of lines are missing.

Here is the output:

What I did wrong ?

You're dilating the original image dilate(image, temp, element);. You should be dilating the eroded one dilate(eroded, temp, element);. — zindarod
– zindarod, Commented Nov 6, 2017 at 17:41
opencv contrib has thinning github.com/opencv/opencv_contrib/blob/master/modules/ximgproc/… — sturkmen
– sturkmen, Commented Nov 6, 2017 at 18:46
here you can find another implementation ( i think faster than OpenCV ) — sturkmen
– sturkmen, Commented Nov 6, 2017 at 18:52
@Xoxo you can find another C++ example here, but probably sturkmen's suggestions are better — Miki
– Miki, Commented Nov 6, 2017 at 19:01

Tim Diekmann · Accepted Answer · 2018-07-06 10:03:53Z

-1

Convert img to a black background with white color shape

img -> threshold(img, img, 128, 255, THRESHOLD_BINARY_INV);

edited Jul 6, 2018 at 10:03

Tim Diekmann

8,60411 gold badges48 silver badges72 bronze badges

answered Jul 6, 2018 at 7:01

user10041013

1

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