opencv直方图对比示例

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直方图对比，显示两张图片的相似度

函数：compareHist();

c++: double compareHist(InputArray H1,InputArray H2,int method);

method:

1.相关， Correlation (method=CV_COMP_CORREL) 方法1越趋近于1的时候基本图与样例图的相似度越近；

2.卡方， Chi-Square (method=CV_COMP_CHISQR) 方2法越趋近于0的时候基本图与样例图的相似度越近；

3.直方相交， Intersection (method=CV_COMP_INTERSETC) 方法3越趋近于58.69的时候基本图与样例图的相似度越近；

4.距离， Bhattacharyya (method=CV_COMP_BHATTACHARYYA) 方法4越趋近于0的时候基本图与样例图的相似度越近；

实例程序代码：

#include "opencv2/objdetect/objdetect.hpp"#include "opencv2/videoio/videoio.hpp"#include "opencv2/highgui/highgui.hpp"#include "opencv2/imgproc/imgproc.hpp"#include <iostream>using namespace std;using namespace cv;int main(int argc, char const *argv[]){Mat frame,hsv,srcImage_base,hsv_base;VideoCapture video;video.open(0);while(1){srcImage_base=imread("base.jpg",1);video.read(frame);cvtColor(frame,hsv,COLOR_BGR2HSV);cvtColor(srcImage_base,hsv_base,COLOR_BGR2HSV);int h_bins=50;int s_bins=60;int histsize[]={h_bins,s_bins};float h_ranges[]={0, 256};float s_ranges[]={0, 180};const float* ranges[]={h_ranges,s_ranges};int channels[]={0,1}; MatND frame_hist; MatND srcImage_base_hist; calcHist( &hsv_base, 1, channels, Mat(), srcImage_base_hist, 2, histSize, ranges, true,false ); normalize( srcImage_base_hist, srcImage_base_hist, 0, 1, NORM_MINMAX, -1, Mat() ); calcHist( &hsv, 1, channels, Mat(), frame_hist, 2, histSize, ranges, true,false ); normalize( frame_hist, frame_hist, 0, 1, NORM_MINMAX, -1, Mat() ); double base_frame=compareHist( srcImage_base_hist,frame_hist,0); count<<"base_frame="<<base_frame<<endl; waitKey(0);}return 0;}

注释：其实base.jpg是基础图片，本例程采用的在实时视频流中检测：

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