opencv学习笔记（六）直方图比较图片相似度

 

opencv学习笔记（六）直方图比较图片相似度

　　opencv提供了API来比较图片的相似程度，使我们很简单的就能对2个图片进行比较，这就是直方图的比较，直方图英文是histogram, 原理就是就是将图片转换成直方图，然后对直方图进行比较，在某些程度，真实地反映了图片的相似度。

代码如下：

#include <iostream>
#include <cv.h>
#include <highgui.h>
using namespace std;
using namespace cv;

int main(void)
{
    Mat pic1 = imread("pic1.jpg");
    Mat pic2 = imread("pic2.jpg");
    //计算相似度
    if (pic2.channels() == 1) {//单通道时，
    int histSize = 256;
    float range[] = { 0, 256 };
    const float* histRange = { range };
    bool uniform = true;
    bool accumulate = false;
            
    cv::Mat hist1, hist2;
            
    cv::calcHist(&pic2, 1, 0, cv::Mat(), hist1, 1, &histSize, &histRange, uniform, accumulate);
    cv::normalize(hist1, hist1, 0, 1, cv::NORM_MINMAX, -1, cv::Mat());
            
    cv::calcHist(&pic1, 1, 0, cv::Mat(), hist2, 1, &histSize, &histRange, uniform, accumulate);
    cv::normalize(hist2, hist2, 0, 1, cv::NORM_MINMAX, -1, cv::Mat());
            
    double dSimilarity = cv::compareHist(hist1, hist2, CV_COMP_CORREL);//,CV_COMP_CHISQR,CV_COMP_INTERSECT,CV_COMP_BHATTACHARYYA    CV_COMP_CORREL
            
    cout << "similarity = " << dSimilarity << endl;
    }
    else {//三通道时
        cv::cvtColor(pic2, pic2, cv::COLOR_BGR2HSV);
        cv::cvtColor(pic1, pic1, cv::COLOR_BGR2HSV);
            
    int h_bins = 50, s_bins = 60;
    int histSize[] = { h_bins, s_bins };
    float h_ranges[] = { 0, 180 };
    float s_ranges[] = { 0, 256 };
    const float* ranges[] = { h_ranges, s_ranges };
    int channels[] = { 0, 1 };
            
    cv::MatND hist1, hist2;
            
    cv::calcHist(&pic2, 1, channels, cv::Mat(), hist1, 2, histSize, ranges, true, false);
    cv::normalize(hist1, hist1, 0, 1, cv::NORM_MINMAX, -1, cv::Mat());
            
    cv::calcHist(&pic1, 1, channels, cv::Mat(), hist2, 2, histSize, ranges, true, false);
    cv::normalize(hist2, hist2, 0, 1, cv::NORM_MINMAX, -1, cv::Mat());
            
    double dSimilarity = cv::compareHist(hist1, hist2, CV_COMP_CORREL); //,CV_COMP_CHISQR,CV_COMP_INTERSECT,CV_COMP_BHATTACHARYYA  CV_COMP_CORREL
            
    cout << "similarity = " << dSimilarity << endl;
    }
    waitKey(0);
    return 1;    

}

　　pic1:

　　

　　pic2:

　　

　　使用相关系数法（CV_COMP_CORREL）进行图片相似度比较时，取值范围为[-1,1]；越接近1说明两幅图片越相似；

　　比较pic1与pic2得到的结果为：

　　similarity =0.926247

　　pic与本身进行比较时，

　　similarity =1