转自
终于到了有实际应用的功能了，有2张图片，里面各有一个人脸，我的目的是比较这两个人脸的相似度，这里用到了facedetect的功能，还有图像转换，图像剪切，以及直方图的比较。具体流程是:
1。分别用facedetect功能将两张图片中的人脸检测出来
2。将人脸部分的图片剪切出来，存到两张只有人脸的图片里。
3。将这两张人脸图片转换成单通道的图像
4。使用直方图比较这两张单通道的人脸图像，得出相似度。
这里对图的要求还是比较高的，光线和姿势不能有差别，脸的垂直或者左右角度偏差就会影响比较，但和两张图片的大小关系不大，本人觉得较适合于证件照的对比。
下面是代码，其中haarcascade_frontalface_alt.xml是OpenCV里facedetect例子用的样本。 比较的是srcImage和targetImage对应的文件.
还有下面是IplImage和Mat混用，纯当熟悉这两个类了。
[cpp]view plaincopy[cpp]view plaincopy
[cpp]view plaincopy#include"opencv/cv.hpp" #include"opencv2/objdetect/objdetect.hpp" #include"opencv2/highgui/highgui.hpp" #include"opencv2/imgproc/imgproc.hpp" #include<iostream> #include<stdio.h> usingnamespacestd; usingnamespacecv; StringcascadeName="D:\\OpenCV-2.4.2\\data\\haarcascades\\haarcascade_frontalface_alt.xml"; IplImage*cutImage(IplImage*src,CvRectrect){ cvSetImageROI(src,rect); IplImage*dst=cvCreateImage(cvSize(rect.width,rect.height), src->depth, src->nChannels); cvCopy(src,dst,0); cvResetImageROI(src); returndst; } IplImage*detect(Mat&img,CascadeClassifier&cascade,doublescale) { inti=0; doublet=0; vector<Rect>faces; Matgray,smallImg(cvRound(img.rows/scale),cvRound(img.cols/scale),CV_8UC1); cvtColor(img,gray,CV_BGR2GRAY); resize(gray,smallImg,smallImg.size(),0,0,INTER_LINEAR); equalizeHist(smallImg,smallImg); t=(double)cvGetTickCount(); cascade.detectMultiScale(smallImg,faces, 1.3,2,CV_HAAR_SCALE_IMAGE, Size(30,30)); t=(double)cvGetTickCount()-t; printf("detectiontime=%gms\n",t/((double)cvGetTickFrequency()*1000.)); for(vector<Rect>::const_iteratorr=faces.begin();r!=faces.end();r++,i++) { IplImage*temp=cutImage(&(IplImage(img)),cvRect(r->x,r->y,r->width,r->height)); returntemp; } returnNULL; } //画直方图用 intHistogramBins=256; floatHistogramRange1[2]={0,255}; float*HistogramRange[1]={&HistogramRange1[0]}; intCompareHist(IplImage*image1,IplImage*image2) { IplImage*srcImage; IplImage*targetImage; if(image1->nChannels!=1){ srcImage=cvCreateImage(cvSize(image1->width,image1->height),image1->depth,1); cvCvtColor(image1,srcImage,CV_BGR2GRAY); }else{ srcImage=image1; } if(image2->nChannels!=1){ targetImage=cvCreateImage(cvSize(image2->width,image2->height),srcImage->depth,1); cvCvtColor(image2,targetImage,CV_BGR2GRAY); }else{ targetImage=image2; } CvHistogram*Histogram1=cvCreateHist(1,&HistogramBins,CV_HIST_ARRAY,HistogramRange); CvHistogram*Histogram2=cvCreateHist(1,&HistogramBins,CV_HIST_ARRAY,HistogramRange); cvCalcHist(&srcImage,Histogram1); cvCalcHist(&targetImage,Histogram2); cvNormalizeHist(Histogram1,1); cvNormalizeHist(Histogram2,1); //CV_COMP_CHISQR,CV_COMP_BHATTACHARYYA这两种都可以用来做直方图的比较，值越小，说明图形越相似 printf("CV_COMP_CHISQR:%.4f\n",cvCompareHist(Histogram1,Histogram2,CV_COMP_CHISQR)); printf("CV_COMP_BHATTACHARYYA:%.4f\n",cvCompareHist(Histogram1,Histogram2,CV_COMP_BHATTACHARYYA)); //CV_COMP_CORREL,CV_COMP_INTERSECT这两种直方图的比较，值越大，说明图形越相似 printf("CV_COMP_CORREL:%.4f\n",cvCompareHist(Histogram1,Histogram2,CV_COMP_CORREL)); printf("CV_COMP_INTERSECT:%.4f\n",cvCompareHist(Histogram1,Histogram2,CV_COMP_INTERSECT)); cvReleaseHist(&Histogram1); cvReleaseHist(&Histogram2); if(image1->nChannels!=1){ cvReleaseImage(&srcImage); } if(image2->nChannels!=1){ cvReleaseImage(&targetImage); } return0; } StringsrcImage="d:\\ldh1.jpg"; StringtargetImage="d:\\ldh5.jpg"; intmain(intargc,char*argv[]) { CascadeClassifiercascade; namedWindow("image1"); namedWindow("image2"); if(!cascade.load(cascadeName)) { return-1; } MatsrcImg,targetImg; IplImage*faceImage1; IplImage*faceImage2; srcImg=imread(srcImage); targetImg=imread(targetImage); faceImage1=detect(srcImg,cascade,1); if(faceImage1==NULL){ return-1; } //cvSaveImage("d:\\face.jpg",faceImage1,0); faceImage2=detect(targetImg,cascade,1); if(faceImage2==NULL){ return-1; } //cvSaveImage("d:\\face1.jpg",faceImage2,0); imshow("image1",Mat(faceImage1)); imshow("image2",Mat(faceImage2)); CompareHist(faceImage1,faceImage2); cvWaitKey(0); cvReleaseImage(&faceImage1); cvReleaseImage(&faceImage2); return0; }
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