使用OpenCV在c++中图像的绿色组件的直方图。

I want to create a histogram for an green component of an image in c++ using OpenCV. The following code is working fine for color image but once i split the image into its RGB component and using the green component to call calcHist function, I am getting the following error.

我想用OpenCV在c++中创建一个绿色组件的直方图。下面的代码对于彩色图像来说是可行的，但是一旦我将图像分割为RGB组件，并使用绿色组件调用calcHist函数，我将得到以下错误。

OpenCV Error: Assertion failed (j < nimages) in histPrepareImages, file /root/src/OpenCV-2.4.1/modules/imgproc/src/histogram.cpp, line 148 terminate called after throwing an instance of 'cv::Exception' what(): /root/src/OpenCV-2.4.1/modules/imgproc/src/histogram.cpp:148: error: (-215) j < nimages in function histPrepareImages Aborted (core dumped)

OpenCV错误:在histprepareimage，文件/ root/src/opencv -2.4.1/模块/imgproc/src/直方图上断言失败(j < nimage)。cpp，第148行终止调用，在抛出了一个“cv::Exception”的实例后，该函数为:/root/ src/opencv -2.4.1/模块/imgproc/src/直方图。cpp:148:错误:(-215)j < nimage in function histprepareimage Aborted (core dump)

Here is my code for the same. I took two images to create the histogram. Anyone pls help so solve this problem.

这是我的代码。我用两个图像来创建直方图。任何人都可以帮助解决这个问题。

#include <cv.h>
#include <highgui.h>

using namespace cv;

int main( int argc, char** argv )
{
    Mat src,src1, hsv, hsv1;
    if( argc != 3 || !(src=imread(argv[1], 1)).data || !(src=imread(argv[2], 1)).data)
        return -1;

    std::vector<cv::Mat> three_channels;
    cv::split(src,three_channels);

    std::vector<cv::Mat> three_channels1;
    cv::split(src1,three_channels1);


    //cvtColor(src, hsv, CV_BGR2HSV);
    //cvtColor(src1, hsv1, CV_BGR2HSV);

    // Quantize the hue to 30 levels
    // and the saturation to 32 levels
    int hbins = 30, sbins = 32;
    int histSize[] = {hbins, sbins};
    // hue varies from 0 to 179, see cvtColor
    float hranges[] = { 0, 180 };
    // saturation varies from 0 (black-gray-white) to
    // 255 (pure spectrum color)
    float sranges[] = { 0, 256 };
    const float* ranges[] = { hranges, sranges };
    MatND hist, hist1, difference;
    // we compute the histogram from the 0-th and 1-st channels
    int channels[] = {0, 1};

    calcHist( &three_channels[1], 1, channels, Mat(), // do not use mask
            hist, 2, histSize, ranges,
            true, // the histogram is uniform
            false );
    calcHist( &three_channels1[1], 1, channels, Mat(), // do not use mask
            hist1, 2, histSize, ranges,
            true, // the histogram is uniform
            false );
    double maxVal=0;
    minMaxLoc(hist, 0, &maxVal, 0, 0);
    minMaxLoc(hist1, 0, &maxVal, 0, 0);

    int scale = 10;
    Mat histImg = Mat::zeros(sbins*scale, hbins*10, CV_8UC3);
    Mat hist1Img = Mat::zeros(sbins*scale, hbins*10, CV_8UC3);
    Mat hist2Img = Mat::zeros(sbins*scale, hbins*10, CV_8UC3);

    double hist_diff =0;    
    hist_diff = compareHist(hist, hist1, CV_COMP_CORREL);

    absdiff(hist, hist1, difference);

    printf("\nHist Diff:   %f\n", hist_diff);

    for( int h = 0; h < hbins; h++ )
        for( int s = 0; s < sbins; s++ )
        {
            float binVal = hist.at<float>(h, s);
            int intensity = cvRound(binVal*255/maxVal);
            rectangle( histImg, Point(h*scale, s*scale),
                    Point( (h+1)*scale - 1, (s+1)*scale - 1),
                    Scalar::all(intensity),
                    CV_FILLED );
        }
    for( int h = 0; h < hbins; h++ )
        for( int s = 0; s < sbins; s++ )
        {
            float binVal = hist1.at<float>(h, s);
            int intensity = cvRound(binVal*255/maxVal);
            rectangle( hist1Img, Point(h*scale, s*scale),
                    Point( (h+1)*scale - 1, (s+1)*scale - 1),
                    Scalar::all(intensity),
                    CV_FILLED );
        }

    for( int h = 0; h < hbins; h++ )
        for( int s = 0; s < sbins; s++ )
        {
            float binVal = difference.at<float>(h, s);
            int intensity = cvRound(binVal*255/maxVal);
            rectangle( hist2Img, Point(h*scale, s*scale),
                    Point( (h+1)*scale - 1, (s+1)*scale - 1),
                    Scalar::all(intensity),
                    CV_FILLED );
        }


    namedWindow( "Source", 1 );
    imshow( "Source", src );

    namedWindow( "H-S Histogram", 1 );
    imshow( "H-S Histogram", histImg );

    namedWindow( "H-S Histogram1", 1 );
    imshow( "H-S Histogram1", hist1Img );

    namedWindow( "H-S Histogram2", 1 );
    imshow( "H-S Histogram2", hist2Img );
    waitKey();
}

1 个解决方案

#1

You're trying to calculate the histogram of two channels (0 and 1) from an image that has only one channel, as you splitted it.

您试图计算两个通道(0和1)的直方图，这两个通道只有一个通道，您将它分割开来。

I did not look at your code in detail, but I guess you could omit the splitting and pass src/src1 to calcHist instead of three_channels[1]/three_channels1[1], setting channels = {1}

我没有详细查看您的代码，但是我想您可以省略拆分并将src/src1传递给calcHist，而不是three_channels[1] [1]， {1}

EDIT

编辑

In your code, change channels = {0,1} to channels{0}, you should not get any errors. You're passing a single-channel image to calcHist(), that's why you should only use channel 0 (the only one). By passing three_channels[1] as input image, you're making sure that you're actually analysing the second channel of your input image.

在您的代码中，更改通道={0,1}为通道{0}，您不应该得到任何错误。您将一个单通道映像传递给calcHist()，这就是为什么您应该只使用channel 0(唯一的)。通过将three_channel[1]作为输入图像，您将确保实际分析输入图像的第二个通道。

OR do the following:

或执行以下操作:

    int channels[] = {1};

    calcHist( &src, 1, channels, Mat(), // do not use mask
        hist, 2, histSize, ranges,
        true, // the histogram is uniform
        false );

You don't need to cv::split(src,three_channels) anymore.

您不需要再使用cv::split(src,three_channels)。

That's two versions that compile, but you actually want to compute a green (1D) histogram and not a 2D histogram. So here's your edited code, that (hopefully) does, what you want:

这是编译的两个版本，但实际上您需要计算一个绿色(1D)直方图，而不是一个2D直方图。这是你编辑过的代码，(希望)你想要的是:

int main( int argc, char** argv )
{
    Mat src,src1;
    if( argc != 3 || !(src=imread(argv[1], 1)).data || !(src=imread(argv[2], 1)).data)
            return -1;



    // Quantize the green to 30 levels
    int greenbins = 30;
    int histSize[] = {greenbins};
    // green varies from 0 to 255 (pure spectrum color)
    float greenranges[] = { 0, 256 };
    const float* ranges[] = { greenranges };
    MatND hist, hist1, difference;
    // we compute the histogram from the 2nd channel (green, index is 1)
    int channels[] = {1};

    calcHist( &src, 1, channels, Mat(), // do not use mask
            hist, 1, histSize, ranges,
            true, // the histogram is uniform
            false );
    calcHist( &src1, 1, channels, Mat(), // do not use mask
            hist1, 1, histSize, ranges,
            true, // the histogram is uniform
            false );
    double maxVal1=0;
    double maxVal2 =0;
    minMaxLoc(hist, 0, &maxVal1, 0, 0);
    minMaxLoc(hist1, 0, &maxVal2, 0, 0);
    double maxVal = max(maxVal1, maxVal2);

    int scale = 10;
    int width = 50;
    Mat histImg = Mat::zeros(greenbins*scale, width, CV_8UC3);
    Mat hist1Img = Mat::zeros(greenbins*scale, width, CV_8UC3);
    Mat hist2Img = Mat::zeros(greenbins*scale, width, CV_8UC3);

    double hist_diff =0;    
    hist_diff = compareHist(hist, hist1, CV_COMP_CORREL);

    absdiff(hist, hist1, difference);

    printf("\nHist Diff:   %f\n", hist_diff);

    for( int h = 0; h<greenbins; ++h)
    {
        float binVal = hist.at<float>(h);
        int intensity = cvRound(binVal*255/maxVal);
        rectangle( histImg, Point(0, h*scale),
                    Point(width, (h+1)*scale),
                    Scalar::all(intensity),
                    CV_FILLED );
    }
    for( int h = 0; h<greenbins; ++h)
    {
        float binVal = hist1.at<float>(h);
        int intensity = cvRound(binVal*255/maxVal);
        rectangle( hist1Img, Point(0, h*scale),
                    Point(width, (h+1)*scale),
                    Scalar::all(intensity),
                    CV_FILLED );
    }

    for(int h = 0; h < greenbins; ++h)
    {
        float binVal = difference.at<float>(h);
        int intensity = cvRound(binVal*255/maxVal);
        rectangle( hist2Img, Point(0, h*scale),
                    Point(width, (h+1)*scale),
                    Scalar::all(intensity),
                    CV_FILLED );
    }

    imshow( "Source", src );
    imshow( "Source1", src1 );

    imshow( "src1 green Histogram", histImg );

    imshow( "src2 green Histogram", hist1Img );

    imshow( "diff green Histogram", hist2Img );
    waitKey();
}