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OpenCV Tutorials —— Histogram Comparison

2024-08-03 19:07:49   224人阅读

直方图匹配

 

OpenCV implements the function compareHist to perform a comparison.

  1. 1，Correlation ( CV_COMP_CORREL )

    d(H_1,H_2) = \frac{\sum_I (H_1(I) - \bar{H_1}) (H_2(I) - \bar{H_2})}{\sqrt{\sum_I(H_1(I) - \bar{H_1})^2 \sum_I(H_2(I) - \bar{H_2})^2}} 线性相关，完全匹配的数值为1，完全不匹配是-1

    where

    \bar{H_k} = \frac{1}{N} \sum _J H_k(J)

    and N is the total number of histogram bins.

  2. 2，Chi-Square ( CV_COMP_CHISQR )

    3. d(H_1,H_2) = \sum _I \frac{\left(H_1(I)-H_2(I)\right)^2}{H_1(I)} 卡方 ~  完全匹配是0，完全不匹配为无穷

  3. 3，Intersection ( method=CV_COMP_INTERSECT )

    d(H_1,H_2) = \sum _I \min (H_1(I), H_2(I))  相交 ~~ 完全匹配是1，完全不匹配是0

  4. 4，Bhattacharyya distance ( CV_COMP_BHATTACHARYYA )

    d(H_1,H_2) = \sqrt{1 - \frac{1}{\sqrt{\bar{H_1} \bar{H_2} N^2}} \sum_I \sqrt{H_1(I) \cdot H_2(I)}}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

OpenCV Tutorials —— Histogram Comparison


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