Question

我有一个Mat文件的向量，我想计算它们之间的相关性，以便保持理论上相似的两个mat文件。实际上在这个向量中存储了从图像中检测到的眼睛，因此我试图删除异常值。如何计算两个Mat文件之间的相关性???

编辑：

Mat Detection::hist_calculation(Mat image){

    // Establish the number of bins
    int histSize = 256;

    // Set the ranges
    float range[] = { 0, 256 } ;
    const float* histRange = { range };

    bool uniform = true; bool accumulate = false;

    Mat hist;

    // Compute the histograms:
    calcHist( &image, 1, 0, Mat(), hist, 1, &histSize, &histRange, uniform, accumulate );


    // Draw the histograms for B, G and R
    int hist_w = 512; int hist_h = 400;
    int bin_w = cvRound( (double) hist_w/histSize );

    Mat histImage( hist_h, hist_w, CV_8UC3, Scalar( 0,0,0) );

    normalize(hist, hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );

    for( int i = 1; i < histSize; i++ )
    {
        line( histImage, Point( bin_w*(i-1), hist_h - cvRound(hist.at<float>(i-1)) ) ,
            Point( bin_w*(i),   hist_h - cvRound(hist.at<float>(i))   ) ,
            Scalar( 255, 0, 0), 2, 8, 0  );
    }

    //// Display
    //namedWindow("calcHist Demo", CV_WINDOW_AUTOSIZE );
    //imshow("calcHist Demo", histImage );
    //waitKey(0);

    return hist;
}

double Detection::cvMatHistCorrelation(Mat file1, Mat file2) {

    cvtColor(file1, file1, CV_BGR2GRAY); cvtColor(file2, file2, CV_BGR2GRAY);
    Mat hist1 = hist_calculation(file1);
    Mat hist2 = hist_calculation(file2);

    double autoCorrelation1 = compareHist( hist1, hist1, CV_COMP_BHATTACHARYYA );
    double autoCorrelation2 = compareHist( hist1, hist1, CV_COMP_BHATTACHARYYA );
    double correlation  = compareHist( hist1, hist2, CV_COMP_BHATTACHARYYA );

    cout << "autocorrelation of his1: "<< autoCorrelation1 << endl;
    cout << "autocorrelation of hist2: "<< autoCorrelation2 << endl;
    cout << "correlation between hist1 and hist2: "<< autoCorrelation << endl;

    return correlation;
}

我认为它运作正常。

Answer 1

最好直接计算这两个Mat文件的特征向量的相关性，而不是直接计算Mat数据。

例如，您可以先为每个Mat文件计算RGB / HSV颜色直方图（24d向量，如果每个通道使用8个bin），然后计算这两个直方图向量的相关性。

计算OpenCV中两个Mat文件的相关性

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