Detect Partial Circles In An Image Using Python And Opencv

December 13, 2023 Post a Comment

I took about 220 images of the partial solar eclipse today and plan to put together a timelapse animation of the event. As expected the image of the partially eclipsed Sun jumps ar

Solution 1:

You can try this:

threshold the image
get the largest contour
find the minimum area circle that encloses this contour

Once you find the center and radius, it'll be easier to register. If the radii are different between snapshots, you'll have to resize all circles to a predefined size and adjust the center accordingly in the registration phase.

I tried this in OpenCV and C++.

    Mat im = imread(INPUT_FOLDER_PATH + string("SoFi_400_20141023_163450.jpg"));

    Mat gray;
    cvtColor(im, gray, CV_BGR2GRAY);

    Mat bw;
    threshold(gray, bw, 0, 255, CV_THRESH_BINARY|CV_THRESH_OTSU);

    vector<vector<Point>> contours;
    vector<Vec4i> hierarchy;
    findContours(bw, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));
    /* in actual implementation you'll have to find the largest contour. 
    here i'm just assuming i get one and it's the largest*/for(int idx = 0; idx >= 0; idx = hierarchy[idx][0])
    {
        Point2f center;
        float radius;
        minEnclosingCircle(contours[idx], center, radius);
        cout << idx << " (" << center.x << ", " << center.y << ") : " << radius << endl;

        circle(im, Point(center.x, center.y), radius, Scalar(0, 255, 255), 2);
    }

    imshow("", im);
    waitKey();