opencv - OpenCV Core.MinMaxLocResult 返回什么？

Question

我正在尝试做与这篇文章类似的事情:Getting dominant colour value from HSV Histogram

我有一张图片，想从中提取主色(色调)。我已经到了计算直方图的地步，并从 minMaxLoc 获得了 maxValue。但是我从 Core.MinMaxLocResult 检索的数字完全没有意义。我得到了 806924 和 1067036 之类的东西； Hue 的期望值不应该在 0 到 180 之间吗？

直方图应该归一化吗？为何如此？我见过像“equalizeHist”和“normalize”这样的方法，但真的不知道如何使用这些方法以及它们将如何帮助我。

此外，一旦我得到一个合理的“最常出现的”色相数，我如何将其转换为实际的色相(例如“绿色是该图像中最常出现的颜色”)？是否有标准的 Hue 范围？比如 0-10 是红色，10-20 是紫色等等？

更新:这是我的代码:

    private void processImage(String imgFilename) {
            channels = new MatOfInt[] { new MatOfInt(0), new MatOfInt(1),
            new MatOfInt(2) };
    histSize = new MatOfInt(histSizeNum);
    hRanges = new MatOfFloat(0f, 180f); // hue varies from 0 to 179
    // use openCV stuff to convert from RGB to HLS space
    Mat src = Highgui.imread(imgFilename);
    Mat hls = new Mat();// destination color space
    Imgproc.cvtColor(src, hls, Imgproc.COLOR_RGB2HLS);
    Core.split(hls, hlsChannels);
    Mat hue = hlsChannels.get(0);
    Mat lum = hlsChannels.get(1);
    Mat sat = hlsChannels.get(2);
    // we compute the histogram from the 0-th channel for hue
    Imgproc.calcHist(Arrays.asList(hls), channels[0], new Mat(), hist,
            histSize, hRanges);

     Core.normalize(hist, hist, 0,2, Core.NORM_MINMAX, -1, new Mat());

    Core.MinMaxLocResult result = Core.minMaxLoc(hist);
    // max value should contain the most-recurring Hue value.
    double mostOccurringHue = result.maxVal;
    double leastOccurringHue = result.minVal;
    //double mostOccurringHue = result.maxLoc.x;
    //double leastOccurringHue = result.minLoc.x;

    // print out for sanity checking
    System.out.println("MAX HUE = " + Double.toString(mostOccurringHue) +"\n");
    System.out.println("MIN HUE = " + Double.toString(leastOccurringHue) +"\n");

Answer 1

我没有使用 openCV 的 ibuilt 方法来计算直方图及其归一化，而是编写了自己的代码，因为我们仅为色调 channel 创建直方图。看看我的代码。

int main()
{

    Mat input = imread("jan31/class4Jan31.jpg",1);
    Mat hsv_input;
    int h_bins = 5;
    Mat hist_input = Mat::zeros( 1, h_bins, CV_32FC1);
    int h_range = 179;
    int totalNumberPixels = 0;

    cvtColor(input, hsv_input, CV_RGB2HSV);
    Mat hsv_channels[3];

    split( hsv_input, hsv_channels );

    for (int i=0; i<hsv_channels[0].rows; i++)
    {
        for (int j=0; j<hsv_channels[0].cols; j++)
        {               
            if( (int)hsv_channels[1].at<uchar>(i,j)>10 &&    (int)hsv_channels[1].at<uchar>(i,j)>100)
            {               
                totalNumberPixels++;
                int pixel_value = (int)hsv_channels[0].at<uchar>(i,j);
                int corresponding_bin =  ( pixel_value * h_bins ) / h_range;                
                hist_input.at<float>( 0, corresponding_bin ) = ( hist_input.at<float>( 0, corresponding_bin ) + 1 );                
            }                                                                                       
        }
    }

    cout<<"\n total pixels: "<<totalNumberPixels;

    for(int i=0; i<hist_input.rows; i++)
    {
        for (int j=0; j<hist_input.cols; j++)
        {
            float pixel = hist_input.at<float>(i,j);
            hist_input.at<float>(i,j) = pixel / totalNumberPixels;

            pixel = hist_input.at<float>(i,j);
            cout<<"\n Pixel: "<<pixel;
        }
    }

    cv::waitKey(0);
    return 0;
}