OpenCV之直方图对比

得到图像的直方图之后，通常要用某些具体的标准来比较两个直方图的相似度。要对两个直方图进行比较，首先必须选择一个衡量直方图相似度的对比标准。OpenCV中用compareHsit()函数来比较两个直方图的相似度。

对比直方图：compareHsit()函数

compareHsit()函数用于对两幅直方图进行比较，有两个版本，函数原型：

double compareHist(InputArray H1, InputArray H2, int mathod)

double compareHist(const SparseMat& H1, const SparseMat& H2)

它们的前两个参数是要比较的直方图，第三个是要选择的距离标准，可以选择的有4种方法：

相关，Correlation(method=CV_COMP_CORREL)

卡方，Chi-Square(method=CV_COMP_CHISQR)

直方图相交，intersection(method=CV_COMP_INTERSECT)

Bhattacharyya距离(method=CV_COMP_BAHATTACHARYYA)

代码示例：

#include <iostream>
#include <opencv2/opencv.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>

using namespace cv;
using namespace std;

int main() {
    Mat srcImage_base, hsvImage_base;
    Mat srcImage_test1, hsvImage_test1;
    Mat srcImage_test2, hsvImage_test2;
    Mat hsvImage_halfDown;

    srcImage_base = imread("/Users/dwz/Desktop/cpp/mogu.jpg", 1);
    srcImage_test1 = imread("/Users/dwz/Desktop/cpp/rain.jpg", 1);
    srcImage_test2 = imread("/Users/dwz/Desktop/cpp/1.jpg", 1);

    cvtColor(srcImage_base, hsvImage_base, COLOR_BGR2HSV);
    cvtColor(srcImage_test1, hsvImage_test1, COLOR_BGR2HSV);
    cvtColor(srcImage_test2, hsvImage_test2, COLOR_BGR2HSV);

    hsvImage_halfDown = hsvImage_base(Range(hsvImage_base.rows/2, hsvImage_base.rows-1),  Range(0, hsvImage_base.cols-1));
    int h_bins = 50, 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 baseHist;
    MatND halfDownHist;
    MatND testHist1;
    MatND testHist2;

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

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

    calcHist(&hsvImage_test1, 1, channels, Mat(), testHist1, 2, histSize, ranges, true, false);
    normalize(testHist1, testHist1, 0, 1, NORM_MINMAX, -1, Mat());

    calcHist(&hsvImage_test2, 1, channels, Mat(), testHist2, 2, histSize, ranges, true, false);
    normalize(testHist2, testHist2, 0, 1, NORM_MINMAX, -1, Mat());


    for (int i=0; i< 4; i++)
    {
        int compare_method = i;
        double base_base = compareHist(baseHist, baseHist, compare_method);
        double base_half = compareHist(baseHist, halfDownHist, compare_method);
        double base_test1 = compareHist(baseHist, testHist1, compare_method);
        double base_test2 = compareHist(baseHist, testHist2, compare_method);
        printf("方法[%d]的匹配结果：nn【基准图-基准图】:%f，【基准图-半身图】：%f，【基准图-测试图1】：%f，【基准图-测试图2】：%fn----------------------n",
                i, base_base, base_half, base_test1, base_test2);

    }


    return 0;
}

输入：

输出：

最后

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