直方圖比較

對輸入的兩張圖像計算得到直方圖H1與H2，歸一化到相同的尺度空間,然后可以通過計算H1與H2的之間的距離得到兩個直方圖的相似程度進而比較圖像本身的相似程度辣往。
Opencv提供的比較方法有四種：
Correlation 相關(guān)性比較(CV_COMP_CORREL)
Chi-Square 卡方比較(CV_COMP_CHISQR)
Intersection 十字交叉性(CV_COMP_INTERSECT)
Bhattacharyya distance 巴氏距離(CV_COMP_BHATTACHARYYA )

首先把圖像從RGB色彩空間轉(zhuǎn)換到HSV色彩空間cvtColor
計算圖像的直方圖忧便，然后歸一化到[0~1]之間calcHist和normalize;
使用上述四種比較方法之一進行比較compareHist
compareHist(
InputArray h1, // 直方圖數(shù)據(jù)折联，下同
InputArray H2,
int method// 比較方法锁孟，上述四種方法之一
)

#include "pch.h"
#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>

using namespace std;
using namespace cv;

string convertToString(double d);

int main(int argc, char** argv) {
    Mat base, test1, test2;
    Mat hsvbase, hsvtest1, hsvtest2;
    base = imread("D:/lena.jpg");
    if (!base.data) {
        printf("could not load image...\n");
        return -1;
    }
    test1 = imread("D:/lena3.jpg");
    test2 = imread("D:/lena2.jpg");

    cvtColor(base, hsvbase, CV_BGR2HSV);
    cvtColor(test1, hsvtest1, CV_BGR2HSV);
    cvtColor(test2, hsvtest2, CV_BGR2HSV);

    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 };
    MatND hist_base;
    MatND hist_test1;
    MatND hist_test2;

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

    calcHist(&hsvtest1, 1, channels, Mat(), hist_test1, 2, histSize, ranges, true, false);
    normalize(hist_test1, hist_test1, 0, 1, NORM_MINMAX, -1, Mat());

    calcHist(&hsvtest2, 1, channels, Mat(), hist_test2, 2, histSize, ranges, true, false);
    normalize(hist_test2, hist_test2, 0, 1, NORM_MINMAX, -1, Mat());
    
    double basebase = compareHist(hist_base, hist_base, CV_COMP_CORREL);
    double basetest1 = compareHist(hist_base, hist_test1, CV_COMP_CORREL);
    double basetest2 = compareHist(hist_base, hist_test2, CV_COMP_CORREL);
    double tes1test2 = compareHist(hist_test1, hist_test2, CV_COMP_CORREL);
    printf("test1 compare with test2 correlation value :%f", tes1test2);

    Mat test12;
    test2.copyTo(test12);
    putText(base, convertToString(basebase), Point(50, 50), CV_FONT_HERSHEY_COMPLEX, 1, Scalar(0, 0, 255), 2, CV_AA);
    putText(test1, convertToString(basetest1), Point(50, 50), CV_FONT_HERSHEY_COMPLEX, 1, Scalar(0, 0, 255), 2, CV_AA);
    putText(test2, convertToString(basetest2), Point(50, 50), CV_FONT_HERSHEY_COMPLEX, 1, Scalar(0, 0, 255), 2, CV_AA);
    putText(test12, convertToString(tes1test2), Point(50, 50), CV_FONT_HERSHEY_COMPLEX, 1, Scalar(0, 0, 255), 2, CV_AA);
    
    namedWindow("base", CV_WINDOW_AUTOSIZE);
    namedWindow("test1", CV_WINDOW_AUTOSIZE);
    namedWindow("test2", CV_WINDOW_AUTOSIZE);

    imshow("base", base);
    imshow("test1", test1);
    imshow("test2", test2);
    imshow("test12", test12);

    waitKey(0);
    return 0;
}

string convertToString(double d) {
    ostringstream os;
    if (os << d)
        return os.str();
    return "invalid conversion";
}

效果圖