opencv学习-imgprocess-直方图比较compareHist

opencv中的compareHist函数是用来计算两个直方图相似度，计算的度量方法有4个，分别为Correlation ( CV_COMP_CORREL )相关性，Chi-Square ( CV_COMP_CHISQR ) 卡方，Intersection ( method=CV_COMP_INTERSECT )交集法，Bhattacharyya distance ( CV_COMP_BHATTACHARYYA )常态分布比对的Bhattacharyya距离法。

compareHist函数返回一个数值，相关性方法范围为0到1,1为最好匹配，卡方法和Bhattacharyya距离法是值为0最好，而交集法为值越大越好。

代码如下：

#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 settingssrc_base = imread( argv[1], 1 );src_test1 = imread( argv[2], 1 );src_test2 = imread( argv[3], 1 );/// Convert to HSVcvtColor( src_base, hsv_base, CV_BGR2HSV );cvtColor( src_test1, hsv_test1, CV_BGR2HSV );cvtColor( src_test2, hsv_test2, CV_BGR2HSV );hsv_half_down = hsv_base( Range( hsv_base.rows/2, hsv_base.rows - 1 ), Range( 0, hsv_base.cols - 1 ) );/// Using 30 bins for hue and 32 for saturationint h_bins = 50; int s_bins = 60;int histSize[] = { h_bins, s_bins };// hue varies from 0 to 256, saturation from 0 to 180float h_ranges[] = { 0, 256 };float s_ranges[] = { 0, 180 };const float* ranges[] = { h_ranges, s_ranges };// Use the o-th and 1-st channelsint channels[] = { 0, 1 };/// HistogramsMatND hist_base;MatND hist_half_down;MatND hist_test1;MatND hist_test2;/// Calculate the histograms for the HSV imagescalcHist( &hsv_base, 1, channels, Mat(), hist_base, 2, histSize, ranges, true, false );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 methodsfor( 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;}