Opencv multiple circle detection in a image

edit

Try the DistanceTransform, it's another good method for circle detection in binary images.

This example should help.

Inevitably, we need to consider the characteristics of "circle" and try SimpleBlobDetector to implement it. The changes also include canceling the parameters of the basic morphological transformation, or directly canceling the morphological change.

#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include <opencv2/features2d.hpp>

void main()
{
    const cv::Mat in = cv::imread("15996646131571621.jpg");
    cv::Mat src;
    cv::dilate(in, src, cv::Mat());
    cv::erode(src, src, cv::Mat());

    cv::Mat hsv;
    cv::cvtColor(src, hsv, cv::COLOR_BGR2HSV);

    std::vector<cv::Mat> split_s;
    cv::split(hsv, split_s);
    split_s[1] = split_s[1] > 70;

    cv::SimpleBlobDetector::Params params;
    params.filterByColor = false;
    params.minThreshold = 120;
    std::vector<cv::KeyPoint> keypoints;
    cv::Ptr<cv::SimpleBlobDetector> detector = cv::SimpleBlobDetector::create(params);
    detector->detect(split_s[1], keypoints);
    cv::drawKeypoints(in, keypoints, in, cv::Scalar(0, 0, 255), cv::DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
    cv::imshow("result", in);
    cv::waitKey();
}

EDIT : there is an open source project OpenCFU

here is just a simple code to show an alternative way

#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"


void main()
{
    const cv::Mat in = cv::imread("15996646131571621.jpg");

    cv::Mat src;
    cv::dilate(in, src, cv::Mat(), cv::Point(-1, -1), 2);
    cv::erode(src, src, cv::Mat(), cv::Point(-1, -1), 2);

    cv::Mat hsv;
    cv::cvtColor(src, hsv, cv::COLOR_BGR2HSV);

    std::vector<cv::Mat> split_s;
    cv::split(hsv, split_s);

    split_s[1] = split_s[1] > 70;
    cv::dilate(split_s[1], split_s[1], cv::Mat());

    std::vector<std::vector<cv::Point> > contours;
    findContours(split_s[1], contours, cv::RETR_TREE, cv::CHAIN_APPROX_SIMPLE);

    for (size_t i = 0; i < contours.size(); i++)
    {
        cv::Rect r = cv::boundingRect(contours[i]);

        cv::Mat resized;
        cv::resize(in(r), resized, cv::Size(5, 5), 0, 0);
        cv::Scalar mean_s = cv::mean(resized);

        if( (mean_s[0] > 120 ) & (mean_s[0]< 200) )
        {
            cv::drawContours(in, contours, i, cv::Scalar(0, 255, 0), 1);
            cv::rectangle(in, r, cv::Scalar(0, 0, 255), 1);
        }
    }

    cv::imshow("result", in);
    cv::waitKey();
}