《学习OpenCV》第七章直方图(练习7.2)

给定三幅在书中讨论的不同光照条件下的手图像，利用cvCalcHist()来获得室内拍照的手的色肤直方图

分别给定2维、8维、16维、32维、256维进行运算

#include <iostream>#include <opencv2/opencv.hpp>#include <opencv2/highgui.hpp>using namespace std;using namespace cv;#define cvQueryHistValue_1D( hist, idx0 )   cvGetReal1D( (hist)->bins, (idx0) )#define cvQueryHistValue_2D( hist, idx0 , idx1 )   cvGetReal2D( (hist)->bins, (idx0) , (idx1))#define binNum 2   //   每一位幅bin的大小/*画直方图*/void DisplayHistogram(CvHistogram * hist , char * windName){    if(!hist || !windName)    {        return;    }    int scale = 100; //缩放比例    int h_bins = hist->mat.dim[0].size;    int s_bins = hist->mat.dim[1].size;    IplImage * histImg = cvCreateImage(cvSize(h_bins * scale , s_bins * scale), 8, 3);    cvSetZero(histImg);    //显示直方图    float max_value = 0;    float bin_value = 0;    int   intensity = 0;    cvGetMinMaxHistValue(hist, 0, &max_value,0,0);    for(int i = 0;i<h_bins;i++)    {        for(int j = 0;j<s_bins;j++)        {            bin_value = cvQueryHistValue_2D( hist, i, j);            intensity = cvRound(bin_value * 255 / max_value);            cvRectangle(histImg, cvPoint(i*scale, j*scale), cvPoint((i+1)*scale-1, (j+1)*scale-1),                                                CV_RGB(intensity, intensity, intensity),CV_FILLED);                    }    }    cvNamedWindow(windName);    cvShowImage(windName, histImg);}int main(int argc, const char * argv[]) {    /*1、加载图片*/    const char filename1[] = "/Users/linwang/Downloads/hand1.jpg";    const char filename2[] = "/Users/linwang/Downloads/hand2.jpg";    const char filename3[] = "/Users/linwang/Downloads/hand3.jpg";    IplImage * Img_hand1 = cvLoadImage(filename1);    IplImage * Img_hand2 = cvLoadImage(filename2);    IplImage * Img_hand3 = cvLoadImage(filename3);        /*2、缩放0.3倍*/    float scale = 0.3;    IplImage * dst_hand1 = cvCreateImage(cvSize(Img_hand1->width * scale, Img_hand1->height * scale),                                         Img_hand1->depth, Img_hand1->nChannels);        IplImage * dst_hand2 = cvCreateImage(cvSize(Img_hand2->width * scale, Img_hand2->height * scale),                                         Img_hand2->depth, Img_hand2->nChannels);        IplImage * dst_hand3 = cvCreateImage(cvSize(Img_hand3->width * scale, Img_hand3->height * scale),                                         Img_hand3->depth, Img_hand3->nChannels);        cvResize(Img_hand1, dst_hand1);    cvResize(Img_hand2, dst_hand2);    cvResize(Img_hand3, dst_hand3);        /*3、显示当前的图片*/    cvNamedWindow("Hand1");    cvNamedWindow("Hand2");    cvNamedWindow("Hand3");        cvShowImage("Hand1", dst_hand1);    cvShowImage("Hand2", dst_hand2);    cvShowImage("Hand3", dst_hand3);        /*4、分别创建三幅手势图像的HSV空间图像单元*/    IplImage * Hsv_hand1 = cvCreateImage(cvGetSize(dst_hand1), 8, 3);    IplImage * Hsv_hand2 = cvCreateImage(cvGetSize(dst_hand2), 8, 3);    IplImage * Hsv_hand3 = cvCreateImage(cvGetSize(dst_hand3), 8, 3);    cvSetZero(Hsv_hand1);    cvSetZero(Hsv_hand2);    cvSetZero(Hsv_hand3);        /*5、颜色阈转换，从GRB到HSV*/    cvCvtColor(dst_hand1, Hsv_hand1, CV_RGB2HSV);    cvCvtColor(dst_hand2, Hsv_hand2, CV_RGB2HSV);    cvCvtColor(dst_hand3, Hsv_hand3, CV_RGB2HSV);        /*6、分别创建hsv的三通道*/    IplImage * h_plane1 = cvCreateImage(cvGetSize(dst_hand1), 8, 1);    IplImage * h_plane2 = cvCreateImage(cvGetSize(dst_hand2), 8, 1);    IplImage * h_plane3 = cvCreateImage(cvGetSize(dst_hand3), 8, 1);    IplImage * s_plane1 = cvCreateImage(cvGetSize(dst_hand1), 8, 1);    IplImage * s_plane2 = cvCreateImage(cvGetSize(dst_hand2), 8, 1);    IplImage * s_plane3 = cvCreateImage(cvGetSize(dst_hand3), 8, 1);        IplImage * v_plane1 = cvCreateImage(cvGetSize(dst_hand1), 8, 1);    IplImage * v_plane2 = cvCreateImage(cvGetSize(dst_hand2), 8, 1);    IplImage * v_plane3 = cvCreateImage(cvGetSize(dst_hand3), 8, 1);        cvSplit(Hsv_hand1, h_plane1, s_plane1, v_plane1, 0);    cvSplit(Hsv_hand2, h_plane2, s_plane2, v_plane2, 0);    cvSplit(Hsv_hand3, h_plane3, s_plane3, v_plane3, 0);        /*7、准备床架吧直方图hist*/    IplImage * planes1[] = {h_plane1,s_plane1};    IplImage * planes2[] = {h_plane2,s_plane2};    IplImage * planes3[] = {h_plane3,s_plane3};        int h_bins1 = binNum;    int h_bins2 = binNum;    int h_bins3 = binNum;        int s_bins1 = binNum;    int s_bins2 = binNum;    int s_bins3 = binNum;        CvHistogram * hist1;    CvHistogram * hist2;    CvHistogram * hist3;        int hist_size1[] = {h_bins1,s_bins1};    int hist_size2[] = {h_bins2,s_bins2};    int hist_size3[] = {h_bins3,s_bins3};        float h_ranges1[] = {0,180};    float h_ranges2[] = {0,180};    float h_ranges3[] = {0,180};        float s_ranges1[] = {0,255};    float s_ranges2[] = {0,255};    float s_ranges3[] = {0,255};        float * ranges1[] = {h_ranges1,s_ranges1};    float * ranges2[] = {h_ranges2,s_ranges2};    float * ranges3[] = {h_ranges3,s_ranges3};        hist1 = cvCreateHist(2, hist_size1, CV_HIST_ARRAY,ranges1,1);    hist2 = cvCreateHist(2, hist_size2, CV_HIST_ARRAY,ranges2,1);    hist3 = cvCreateHist(2, hist_size3, CV_HIST_ARRAY,ranges3,1);        /*8、计算直方图并做归一化*/    cvCalcHist(planes1, hist1 , 0 ,0);    cvCalcHist(planes2, hist2 , 0 ,0);    cvCalcHist(planes3, hist3 , 0 ,0);        cvNormalizeHist(hist1, 1.0);    cvNormalizeHist(hist2, 1.0);    cvNormalizeHist(hist3, 1.0);        /*9、显示各种直方图的对比结果*/    cout<<"Bins = "<<binNum<<endl;    double dist1_to_2[4] = {0.0};    double dist1_to_3[4] = {0.0};    double dist2_to_3[4] = {0.0};    char *hist_method[4] = {"相关","卡方","直方图相交","Bhattacharyya距离"};   //依次进行"相关","卡方","直方图相交"，"Bhattacharyya距离" 比较操作，并显示结果    for(int i = 0;i<4;i++)    {        dist1_to_2[i] = cvCompareHist(hist1, hist2, i);        cout<<"Method : "<<hist_method[i]<<"->图像1和图像2的匹配结果-> "<<dist1_to_2[i]<<endl;    }        for(int i = 0;i<4;i++)    {        dist1_to_3[i] = cvCompareHist(hist1, hist3, i);        cout<<"Method : "<<hist_method[i]<<"->图像1和图像3的匹配结果-> "<<dist1_to_3[i]<<endl;    }        for(int i = 0;i<4;i++)    {        dist2_to_3[i] = cvCompareHist(hist2, hist3, i);        cout<<"Method : "<<hist_method[i]<<"->图像2和图像3的匹配结果-> "<<dist2_to_3[i]<<endl;    }        /*10、利用直方图显示各种匹配结果*/    cout<<hist1->mat.dim[0].size<<endl;    cout<<hist1->mat.dim[1].size<<endl;    DisplayHistogram(hist1, "hist1");    DisplayHistogram(hist2, "hist2");    DisplayHistogram(hist3, "hist3");    cvWaitKey(0);        cvReleaseHist(&hist1);    cvReleaseHist(&hist2);    cvReleaseHist(&hist3);    cvDestroyWindow("Hand1");    cvDestroyWindow("Hand2");    cvDestroyWindow("Hand3");    cvReleaseImage(&Img_hand1);    cvReleaseImage(&Img_hand2);    cvReleaseImage(&Img_hand3);    cvReleaseImage(&dst_hand1);    cvReleaseImage(&dst_hand2);    cvReleaseImage(&dst_hand3);    cvReleaseImage(&Hsv_hand1);    cvReleaseImage(&Hsv_hand2);    cvReleaseImage(&Hsv_hand3);    cvReleaseImage(&h_plane1);    cvReleaseImage(&h_plane2);    cvReleaseImage(&h_plane3);    cvReleaseImage(&s_plane1);    cvReleaseImage(&s_plane2);    cvReleaseImage(&s_plane3);    cvReleaseImage(&v_plane1);    cvReleaseImage(&v_plane2);    cvReleaseImage(&v_plane3);    return 1;    }

2维

8维

16维

32维：

256维