opencv simple blob detection, getting some undetected blobs

Question

i've searched a bit online and using the search here on stackoverflow but haven't found quite what i was looking for on this issue. So basicaly i'm using simple blob detection, from opencv, to get the white areas in my image(which is already binary) and in very similar images i get very diferent results in terms of which blobs are detected and which are not, here is an example followed by my parameters when defining simpleblobdetector.

As you can see some of the blobs are not beeing detected, here is my configuration of the detector:

void blobDetect(cv::Mat img) {
    cv::SimpleBlobDetector::Params params;
    if (Daytime) {
        params.minThreshold = 23;
        params.maxThreshold = 25;
    }
    else {

        params.minThreshold = 3;
        params.maxThreshold = 5;
    }
    params.thresholdStep = 1;

    params.filterByColor = true;
    params.blobColor = 255;
    params.filterByArea = true;
    params.minArea = 300;
    params.maxArea = 400000;
    params.filterByCircularity = false;
    //params.minCircularity = "";

    params.filterByConvexity = false;
    //params.minConvexity = "";

    params.filterByInertia = false;
    //params.minInertiaRatio = "";

    cv::Ptr<cv::SimpleBlobDetector> detector = cv::SimpleBlobDetector::create(params);

    std::vector<cv::KeyPoint> keypoints;

    detector->detect(img, keypoints);

    cv::Mat im_with_keypoints;

    std::cout << keypoints.size() << std::endl;

    drawKeypoints(img, keypoints, im_with_keypoints, cv::Scalar(0, 0, 255), cv::DrawMatchesFlags::DRAW_RICH_KEYPOINTS);

    imshow("display4", im_with_keypoints);
}

So i ask, is it because of the shape and size of the blobs?(i doubt this option since in some cases it can find big areas of wierd shapes) I thought simple blob detection could find any group of pixels, is it more apropriate for circular blobs or something like that? should i think about using another algorithm or building my own? or is there a way for me to get around this and increase the accuracy of simple blob detection?

I know those are a lot of questions, but thank you in advance for any help you can give!

Blob detector is pretty old OpenCV, why not find contours and sort by area? — alkasm
– alkasm, Commented Jun 19, 2017 at 15:45
I see what you mean, i will try this out! I figured there would be a better way to aproach this, but since i'm still inexperienced i was having trouble figuring out which way to go! i'll post results :) thank you! — José Matos
– José Matos, Commented Jun 19, 2017 at 15:53

José Matos · Accepted Answer · 2017-06-19 17:21:12Z

2

Just like Alexander Reynolds sugested "Blob detector is pretty old OpenCV, why not find contours and sort by area?"

I used this link to get a starting point.

After having the contours of the image i use this: "if (cv::contourArea(contours[i]) > 500)" to threshold small areas and it works perfectly, plus it works much faster than blobdetection.

Again, Alexander, thank you very much for pointing me in the right direction :)

ps: as sugested, here is the full solution.

void findContours(cv::Mat img) {
    // find contours:
    std::vector<std::vector<cv::Point> > contours;
    std::vector<cv::Vec4i> hierarchy;
    findContours(img, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE);

    // draw contours:
    cv::Mat imgWithContours = cv::Mat::zeros(img.rows, img.cols, CV_8UC3);
    cv::RNG rng(12345);
    for (int i = 0; i < contours.size(); i++)
    {
        if (cv::contourArea(contours[i]) > 500) {
            cv::Scalar color = cv::Scalar(rng.uniform(50, 255), rng.uniform(50, 255), rng.uniform(50, 255));
            drawContours(imgWithContours, contours, i, color, 1, 8, hierarchy, 0);
        }
    }
    imshow("display4", imgWithContours);
}

edited Jun 19, 2017 at 17:21

answered Jun 19, 2017 at 16:23

José Matos

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1 Comment

alkasm Over a year ago

Glad to see that you were able to get it working to your liking! Good work, maybe post your full solution that you used in case others stumble upon this question.

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