Color classification with k-means in OpenCV

Question

I want to cluster a lot of images with the K-Means Algorithm. I want to set up the clusters, so that each cluster represent the dominant color or the hue of the

Answer 1

You can vectorize your image so each row is a set of RGB, and than use cv::kmeans to cluster, something like:

    std::vector imgRGB;
    cv::split(img,imgRGB);
    int k=5;
    int n = img.rows *img.cols;
    cv::Mat img3xN(n,3,CV_8U);
    for(int i=0;i!=3;++i)  
      imgRGB[i].reshape(1,n).copyTo(img3xN.col(i));
    img3xN.convertTo(img3xN,CV_32F);
    cv::Mat bestLables;
    cv::kmeans(img3xN,k,bestLables,cv::TermCriteria(),10,cv::KMEANS_RANDOM_CENTERS );
    bestLables= bestLables.reshape(0,img.rows);
    cv::convertScaleAbs(bestLables,bestLables,int(255/k));
    cv::imshow("result",bestLables);
    cv::waitKey();