轉載至：http://www.cnblogs.com/zsb517/archive/2012/06/20/2556508.html

直方圖反向投影式通過給定的直方圖信息，在圖像找到相應的像素分布區域，opencv提供兩種算法，一個是基于像素的，一個是基于塊的。

使用方法不寫了，可以參考一下幾個網站：

直方圖反向投影參考1

直方圖參考2

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測試例子1：灰度直方圖反向投影

IplImage * image= cvLoadImage("22.jpg"); IplImage * image2= cvLoadImage("2.jpg"); int hist_size=256; float range[] = {0,255}; float* ranges[]={range}; IplImage* gray_plane = cvCreateImage(cvGetSize(image),8,1); cvCvtColor(image,gray_plane,CV_BGR2GRAY); CvHistogram* gray_hist = cvCreateHist(1,&hist_size,CV_HIST_ARRAY,ranges,1); cvCalcHist(&gray_plane,gray_hist,0,0); //cvNormalizeHist(gray_hist,1.0); IplImage* gray_plane2 = cvCreateImage(cvGetSize(image2),8,1); cvCvtColor(image2,gray_plane2,CV_BGR2GRAY); //CvHistogram* gray_hist2 = cvCreateHist(1,&hist_size,CV_HIST_ARRAY,ranges,1); //cvCalcHist(&gray_plane2,gray_hist2,0,0); //cvNormalizeHist(gray_hist2,1.0); IplImage* dst = cvCreateImage(cvGetSize(gray_plane2),IPL_DEPTH_8U,1); cvCalcBackProject(&gray_plane2, dst ,gray_hist); cvEqualizeHist(dst,dst); //產生的圖像太暗，做了一些直方圖均衡cvNamedWindow( "dst"); cvShowImage("dst",dst); cvNamedWindow( "src"); cvShowImage( "src", image2 ); cvNamedWindow( "templ"); cvShowImage( "templ", image ); cvWaitKey();

效果圖：

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第一個圖為源圖像，中間的那個小圖像是產生用于反向投影的直方圖的圖像，最后的用直方圖均衡化后的結果圖像，可以看到，蘋果的像素位置幾被找到了。

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測試例子2：彩色直方圖反向投影測試

IplImage*src= cvLoadImage("myhand2.jpg", 1); IplImage*templ=cvLoadImage("myhand3.jpg",1);cvNamedWindow( "Source" ); cvShowImage( "Source", src ); IplImage* h_plane2 = cvCreateImage( cvGetSize(src), 8, 1 ); IplImage* s_plane2 = cvCreateImage( cvGetSize(src), 8, 1 ); IplImage* v_plane2 = cvCreateImage( cvGetSize(src), 8, 1); IplImage* planes2[] = { h_plane2, s_plane2,v_plane2 };IplImage* hsv2 = cvCreateImage( cvGetSize(src), 8, 3 ); cvCvtColor( src, hsv2, CV_BGR2HSV ); cvSplit( hsv2, h_plane2, s_plane2, v_plane2, 0 ); printf("h%d",h_plane2->widthStep); printf("s%d",h_plane2->widthStep); printf("v%d",h_plane2->widthStep);IplImage* h_plane = cvCreateImage( cvGetSize(templ), 8, 1 ); IplImage* s_plane = cvCreateImage( cvGetSize(templ), 8, 1 ); IplImage* v_plane = cvCreateImage( cvGetSize(templ), 8, 1); IplImage* planes[] = { h_plane, s_plane,v_plane }; IplImage* hsv = cvCreateImage( cvGetSize(templ), 8, 3 ); cvCvtColor( templ, hsv, CV_BGR2HSV ); cvSplit( hsv, h_plane, s_plane, v_plane, 0 ); printf("h%d\n",h_plane->widthStep); printf("s%d\n",s_plane->widthStep); printf("v%d\n",v_plane->widthStep);int h_bins = 16, s_bins = 16,v_bins=16; int hist_size[] = {h_bins, s_bins,v_bins}; float h_ranges[] = {0,255}; float s_ranges[] = {0,255}; float v_ranges[] = {0,255}; float* ranges[] = { h_ranges, s_ranges,v_ranges}; CvHistogram* hist; hist = cvCreateHist( 3, hist_size, CV_HIST_ARRAY, ranges, 1 ); cvCalcHist( planes, hist, 0, 0 ); //1.double a=1.f; //2.cvNormalizeHist(hist,a); //templ's hist is just calculateIplImage*back_project=cvCreateImage(cvGetSize(src),8,1);//!!歸一，把改成，就彈出對話框，說planes的steps不是一致的！cvZero(back_project); //但是我去掉歸一，改成就可以顯示//NOW we begin calculate back projectcvCalcBackProject(planes2,back_project,hist);cvNamedWindow( "back_project" ); cvShowImage( "back_project", back_project ); cvWaitKey(0);

測試結果：

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手的膚色位置基本找到了，但是有一個問題，在做直方圖反向的時候，直方圖分級是16等分，并不是256等分，下圖是32等分和8等分的圖像效果：

????? 32等分??8等分

程序里面使用了SHV分量，也算是膚色檢測的一個實例，里面的顏色區分很明顯，所有采用大一點的區域統計，能更好的找到膚色的位置，如果采用很細的顏色區分，光照的影響也會考慮進去了。

測試例子3：基于塊的直方圖投影

這種方法速度很慢，模版圖像別弄的太大了。

IplImage*src= cvLoadImage("2.jpg", 1); IplImage*templ=cvLoadImage("22.jpg",1);cvNamedWindow( "Source" ); cvShowImage( "Source", src ); IplImage* h_plane2 = cvCreateImage( cvGetSize(src), 8, 1 ); IplImage* s_plane2 = cvCreateImage( cvGetSize(src), 8, 1 ); IplImage* v_plane2 = cvCreateImage( cvGetSize(src), 8, 1); IplImage* planes2[] = { h_plane2, s_plane2,v_plane2 };IplImage* hsv2 = cvCreateImage( cvGetSize(src), 8, 3 ); cvCvtColor( src, hsv2, CV_BGR2HSV ); cvSplit( hsv2, h_plane2, s_plane2, v_plane2, 0 ); printf("h%d",h_plane2->widthStep); printf("s%d",h_plane2->widthStep); printf("v%d",h_plane2->widthStep);IplImage* h_plane = cvCreateImage( cvGetSize(templ), 8, 1 ); IplImage* s_plane = cvCreateImage( cvGetSize(templ), 8, 1 ); IplImage* v_plane = cvCreateImage( cvGetSize(templ), 8, 1); IplImage* planes[] = { h_plane, s_plane,v_plane }; IplImage* hsv = cvCreateImage( cvGetSize(templ), 8, 3 ); cvCvtColor( templ, hsv, CV_BGR2HSV ); cvSplit( hsv, h_plane, s_plane, v_plane, 0 ); printf("h%d\n",h_plane->widthStep); printf("s%d\n",s_plane->widthStep); printf("v%d\n",v_plane->widthStep);int h_bins = 16, s_bins = 16,v_bins=16; int hist_size[] = {h_bins, s_bins,v_bins}; float h_ranges[] = {0,255}; float s_ranges[] = {0,255}; float v_ranges[] = {0,255}; float* ranges[] = { h_ranges, s_ranges,v_ranges}; CvHistogram* hist; hist = cvCreateHist( 3, hist_size, CV_HIST_ARRAY, ranges, 1 ); cvCalcHist( planes, hist, 0, 0 );CvSize temp ; temp.height = src->height - templ->height + 1; temp.width = src->width - templ->width + 1; IplImage*back_project=cvCreateImage(temp,IPL_DEPTH_32F,1);//!!歸一，把改成，就彈出對話框，說planes的steps不是一致的！cvZero(back_project); //但是我去掉歸一，改成就可以顯示 cvCalcBackProjectPatch(planes2, back_project, cvGetSize(templ), hist,CV_COMP_INTERSECT ,1);cvNamedWindow( "back_project" ); cvShowImage( "back_project", back_project ); cvWaitKey(0);

測試圖像：

當模版圖像小雨目標的時候，作為區域檢測器，測試如下：可以找到手區域

當模版等于目標的時候，測試如下：輸出圖像，較亮的部分就是人的頭部大致位置

基于塊的反向，速度太慢了。



轉載于:https://www.cnblogs.com/zfluo/p/5131870.html

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