OpenCV Tutorials —— Histogram Comparison

直方图匹配

OpenCV implements the function compareHist to perform a comparison.

1. 1，Correlation ( CV_COMP_CORREL )

   线性相关，完全匹配的数值为1，完全不匹配是-1

   where

   

   and is the total number of histogram bins.

2. 2，Chi-Square ( CV_COMP_CHISQR )

卡方 ~  完全匹配是0，完全不匹配为无穷

3. 3，Intersection ( method=CV_COMP_INTERSECT )

     相交 ~~ 完全匹配是1，完全不匹配是0

4. 4，Bhattacharyya distance ( CV_COMP_BHATTACHARYYA )

   巴氏距离 ~~ 完全匹配是0，完全不匹配是1

hsv_half_down = hsv_base( Range( hsv_base.rows/2, hsv_base.rows - 1 ), Range( 0, hsv_base.cols - 1 ) );

截取原图像的一半  ———— Range ！！

Code

 

#include "stdafx.h"

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>

using namespace std;
using namespace cv;

/**
 * @function main
 */
int main( int argc, char** argv )
{
    Mat src_base, hsv_base;
    Mat src_test1, hsv_test1;
    Mat src_test2, hsv_test2;
    Mat hsv_half_down;

    /// Load three images with different environment settings
	/*
    if( argc < 4 )
    {
        printf("** Error. Usage: ./compareHist_Demo <image_settings0> <image_setting1> <image_settings2>\n");
        return -1;
    }*/

    src_base = imread( "img1.jpg", 1 );
    src_test1 = imread( "img3.jpg", 1 );
    src_test2 = imread( "img4.jpg", 1 );

    /// Convert to HSV
    cvtColor( src_base, hsv_base, COLOR_BGR2HSV );
    cvtColor( src_test1, hsv_test1, COLOR_BGR2HSV );
    cvtColor( src_test2, hsv_test2, COLOR_BGR2HSV );

    hsv_half_down = hsv_base( Range( hsv_base.rows/2, hsv_base.rows - 1 ), Range( 0, hsv_base.cols - 1 ) );

    /// Using 50 bins for hue and 60 for saturation
    int h_bins = 50; int s_bins = 60;
    int histSize[] = { h_bins, s_bins };

    // hue varies from 0 to 179, saturation from 0 to 255
    float h_ranges[] = { 0, 180 };
    float s_ranges[] = { 0, 256 };

    const float* ranges[] = { h_ranges, s_ranges };

    // Use the o-th and 1-st channels
    int channels[] = { 0, 1 };

    /// Histograms
    MatND hist_base;
    MatND hist_half_down;
    MatND hist_test1;
    MatND hist_test2;

    /// Calculate the histograms for the HSV images
    calcHist( &hsv_base, 1, channels, Mat(), hist_base, 2, histSize, ranges, true, false );		// 2 维直方图
    normalize( hist_base, hist_base, 0, 1, NORM_MINMAX, -1, Mat() );

    calcHist( &hsv_half_down, 1, channels, Mat(), hist_half_down, 2, histSize, ranges, true, false );
    normalize( hist_half_down, hist_half_down, 0, 1, NORM_MINMAX, -1, Mat() );

    calcHist( &hsv_test1, 1, channels, Mat(), hist_test1, 2, histSize, ranges, true, false );
    normalize( hist_test1, hist_test1, 0, 1, NORM_MINMAX, -1, Mat() );

    calcHist( &hsv_test2, 1, channels, Mat(), hist_test2, 2, histSize, ranges, true, false );
    normalize( hist_test2, hist_test2, 0, 1, NORM_MINMAX, -1, Mat() );

    /// Apply the histogram comparison methods
    for( int i = 0; i < 4; i++ )
    {
        int compare_method = i;
        double base_base = compareHist( hist_base, hist_base, compare_method );
        double base_half = compareHist( hist_base, hist_half_down, compare_method );
        double base_test1 = compareHist( hist_base, hist_test1, compare_method );
        double base_test2 = compareHist( hist_base, hist_test2, compare_method );

        printf( " Method [%d] Perfect, Base-Half, Base-Test(1), Base-Test(2) : %f, %f, %f, %f \n", i, base_base, base_half , base_test1, base_test2 );
    }

    printf( "Done \n" );

    return 0;
}

注意：

二维直方图的定义方式

由于 uniform flag 选为 true，所以指定range的上下限之后，它会根据指定的bins均分