opencv2.4.9+vs2013人脸识别环境搭建，眼睛，鼻子，嘴巴等摄像头读取和显示

一 ，环境设置  

      工具： 

•       opencv2.4.9地址：https://sourceforge.net/projects/opencvlibrary/files/opencv-win/2.4.9/opencv-2.4.9.exe/download
•       VS2013自行安装

     1.   安装opencv2.4.9，解压，请务必记住自己解压的路径。以我自己的路径为例D:\

        IplImage* image = cvLoadImage(filename ); //加载图像
if( image )
{
detect_and_draw( image );
cvWaitKey(0);
cvReleaseImage( &image );
}


cvDestroyWindow("result");
cvWaitKey(0);
return 0;
}


void detect_and_draw( IplImage* img ) //检测人脸并画出区域
{
static CvScalar colors[] = //随机生成颜色序列
{
{{0,0,255}},
{{0,128,255}},
{{0,255,255}},
{{0,255,0}},
{{255,128,0}},
{{255,255,0}},
{{255,0,0}},
{{255,0,255}}
};


double scale = 1.3;
IplImage* gray = cvCreateImage( cvSize(img->width,img->height), 8, 1 );
IplImage* small_img = cvCreateImage( cvSize( cvRound (img->width/scale),
cvRound (img->height/scale)),8, 1 );
int i;


cvCvtColor( img, gray, CV_BGR2GRAY );//彩色图转化为灰度图
cvResize( gray, small_img, CV_INTER_LINEAR ); //利用线性插值算法归一化图像
cvEqualizeHist( small_img, small_img ); //直方图均衡化
cvClearMemStorage( storage );


if( cascade )
{
double t = (double)cvGetTickCount();
CvSeq* faces = cvHaarDetectObjects( small_img, cascade, storage,
1.1, 2, 0/*CV_HAAR_DO_CANNY_PRUNING*/,
cvSize(30, 30) );
t = (double)cvGetTickCount() - t;
printf( "detection time = %gms/n", t/((double)cvGetTickFrequency()*1000.) ); //统计人脸定位所用时间
for( i = 0; i <(faces ? faces->total : 0); i++ )
{
CvRect* r = (CvRect*)cvGetSeqElem( faces, i );
CvPoint center;
int radius;
center.x = cvRound((r->x + r->width*0.5)*scale); //圆心
center.y = cvRound((r->y + r->height*0.5)*scale);
radius = cvRound((r->width + r->height)*0.25*scale); //半径
cvCircle( img, center, radius, colors[i%8], 3, 8, 0 ); //用圆形圈出人脸区域
}
}


cvShowImage( "result", img );
cvReleaseImage( &gray );
cvReleaseImage( &small_img );
}

   2.  人脸识别 ———视频

#include "cv.h"  
#include "highgui.h"  


#include   
#include   
#include   
#include   
#include   
#include   
#include   
#include   
#include   
using namespace std;


static CvMemStorage* storage = 0;
static CvHaarClassifierCascade* cascade = 0;


void detect_and_draw(IplImage* image);


const char* cascade_name = "D:/opencv2.4.9/opencv/sources/data/haarcascades/haarcascade_frontalface_alt.xml"; //opencv×Ô´øÈËÁ³Ê¶±ðѵÁ·½á¹û  
/* "haarcascade_profileface.xml";*/


int main()
{
	CvCapture* capture;
	capture = cvCreateCameraCapture(0);
	cvNamedWindow("face", 1);

	cascade = (CvHaarClassifierCascade*)cvLoad(cascade_name, 0, 0, 0);//¼ÓÔØopencv×Ô´øÈËÁ³Ê¶±ðѵÁ·½á¹û  


	if (!cascade)
	{
		fprintf(stderr, "ERROR: Could not load classifier cascade/n");
		//fprintf( stderr,  
		//"Usage: facedetect --cascade=/""/[filename|camera_index]/n" );  
		return -1;
	}
	storage = cvCreateMemStorage(0);
	assert(capture != NULL);
	
	IplImage* frame;
	frame = cvQueryFrame( capture );  //ÏȶÁÒ»´Î¹æ±ÜµôµÚÒ»Ö¡  
	while (1) {
		frame = cvQueryFrame(capture);
		detect_and_draw(frame);
		//if (!frame) break;         //Èç¹û³ÌÐò²»ÄܶÁÈ¡ÉãÏñÍ·£¬ÄÇô½«´Ë¾äɾ³ý»ò¼Ó¸öÅжϼ´²ÉÓÃ×¢Ê͵ôµÄiÓï¾äÓÖ»òÕßÔÚwhileÇ°¶ÁÒ»´Î  
		//if( !frame&i>0 ) break;  
		//if(i>0)  
		cvShowImage("face", frame);
		char c = cvWaitKey(10);
		if (c == 27) break;
		//i++;  
	}
	cvReleaseCapture(&capture);
	cvDestroyWindow("face");
	cvWaitKey(0);
	return 0;

}


void detect_and_draw(IplImage* img) //¼ì²âÈËÁ³²¢»­³öÇøÓò  
{
	static CvScalar colors[] =   //Ëæ»úÉú³ÉÑÕÉ«ÐòÁÐ  
	{
		{ { 0, 0, 255 } },
		{ { 0, 128, 255 } },
		{ { 0, 255, 255 } },
		{ { 0, 255, 0 } },
		{ { 255, 128, 0 } },
		{ { 255, 255, 0 } },
		{ { 255, 0, 0 } },
		{ { 255, 0, 255 } }
	};


	double scale = 1.3;
	IplImage* gray = cvCreateImage(cvSize(img->width, img->height), 8, 1);
	IplImage* small_img = cvCreateImage(cvSize(cvRound(img->width / scale),
		cvRound(img->height / scale)), 8, 1);
	int i;


	cvCvtColor(img, gray, CV_BGR2GRAY);//²Êɫͼת»¯Îª»Ò¶Èͼ  
	cvResize(gray, small_img, CV_INTER_LINEAR); //ÀûÓÃÏßÐÔ²åÖµËã·¨¹éÒ»»¯Í¼Ïñ  
	cvEqualizeHist(small_img, small_img); //Ö±·½Í¼¾ùºâ»¯  
	cvClearMemStorage(storage);


	if (cascade)
	{
		double t = (double)cvGetTickCount();
		CvSeq* faces = cvHaarDetectObjects(small_img, cascade, storage,
			1.1, 2, 0/*CV_HAAR_DO_CANNY_PRUNING*/,
			cvSize(30, 30));
		t = (double)cvGetTickCount() - t;
		printf("detection time = %gms/n", t / ((double)cvGetTickFrequency()*1000.)); //ͳ¼ÆÈËÁ³¶¨Î»ËùÓÃʱ¼ä  
		for (i = 0; i <(faces ? faces->total : 0); i++)
		{
			CvRect* r = (CvRect*)cvGetSeqElem(faces, i);
			CvPoint center;
			int radius;
			center.x = cvRound((r->x + r->width*0.5)*scale); //Ô²ÐÄ  
			center.y = cvRound((r->y + r->height*0.5)*scale);
			radius = cvRound((r->width + r->height)*0.25*scale); //°ë¾¶  
			cvCircle(img, center, radius, colors[i % 8], 3, 8, 0); //ÓÃÔ²ÐÎȦ³öÈËÁ³ÇøÓò  
		}
	}


	//cvShowImage("result", img);
	cvReleaseImage(&gray);
	cvReleaseImage(&small_img);
}

注释：

const char* cascade_name="haarcascade_frontalface_alt2.xml";//分类器的名称
const char* cascade_name1="haarcascade_eye_tree_eyeglasses.xml";//分类器的名称
const char* cascade_name2="haarcascade_frontalface_alt_tree.xml";//分类器的名称
const char* cascade_name3="haarcascade_mcs_mouth.xml";//分类器的名称
const char* cascade_name4="haarcascade_mcs_nose.xml";//分类器的名称

这是不同的分类器，你可以在你安装的OpenCV中找到。如D:\Program Files\OpenCV2.0\vs2008\data\haarcascades

不同分类器能够帮助你识别不同的部分，如眼睛，鼻子和嘴，更多的需要自己去探索吧。

注释：

  把圆形转换成矩形：

pt1.x = r->x*scale; 
pt2.x = (r->x+r->width)*scale; 
pt1.y = r->y*scale; 
pt2.y = (r->y+r->height)*scale; 
cvRectangle( img, pt1, pt2, CV_RGB(255,0,0), 3, 8, 0 ); 

pt1 : 矩形左上角

pt2:  矩形右下角

只需把  

cvCircle(img, center, radius, colors[i % 8], 3, 8, 0); //用圆形圈出人脸区域  

换成

cvRectangle(img, cvPoint(r->x*scale, r->y*scale), cvPoint((r->x + r->width)*scale, (r->x + r->height)*scale), cvScalar(0, 0, 255), 2, 8, 0);