OpenCV学习笔记3:找出人脸，同时比较两张图片中的人脸相似度

 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。

#include "opencv/cv.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"

#include
#include

using namespace std;
using namespace cv;

String cascadeName = "D:\\OpenCV-2.4.2\\data\\haarcascades\\haarcascade_frontalface_alt.xml";

IplImage* cutImage(IplImage* src, CvRect rect) {
    cvSetImageROI(src, rect);
    IplImage* dst = cvCreateImage(cvSize(rect.width, rect.height),
            src->depth,
            src->nChannels);

    cvCopy(src,dst,0);
    cvResetImageROI(src);
    return dst;
}

IplImage* detect( Mat& img, CascadeClassifier& cascade, double scale)
{
    int i = 0;
    double t = 0;
    vector faces;
    Mat gray, 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( "detection time = %g ms\n", t/((double)cvGetTickFrequency()*1000.) );
    for( vector::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
    {
        IplImage* temp = cutImage(&(IplImage(img)), cvRect(r->x, r->y, r->width, r->height));
        return temp;
    }

    return NULL;
}
//画直方图用
int HistogramBins = 256;
float HistogramRange1[2]={0,255};
float *HistogramRange[1]={&HistogramRange1[0]};
int CompareHist(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);
    }
    return 0;
}
String srcImage = "d:\\ldh1.jpg";
String targetImage = "d:\\ldh5.jpg";
int main(int argc, char* argv[])
{
    CascadeClassifier cascade;
    namedWindow("image1");
    namedWindow("image2");
    if( !cascade.load( cascadeName ) )
    {
        return -1;
    }

    Mat srcImg, 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);
    return 0;
}
http://blog.csdn.net/nicebooks/article/details/8175002