Opencv基于VC++开发的视频入侵检测预警程序.rar

#pragma comment(linker, "/subsystem:\"windows\" /entry:\"mainCRTStartup\"") #include "cv.h" #include "highgui.h" #include <stdlib.h> #include <time.h> #include <math.h> #include <ctype.h> #include <stdio.h> #include <string.h> //#include <iostream.h> //using namespace std; double TrianglArea( int x1,int y1,int x2, int y2, int x3,int y3); double SquArea(int x1,int y1,int x2, int y2, int x3,int y3,int x4,int y4); void detect_face(IplImage* dst_img,int* count); // various tracking parameters (in seconds) const double MHI_DURATION = 0.5; const double MAX_TIME_DELTA = 0.5; const double MIN_TIME_DELTA = 0.05; const int N = 3; // const int CONTOUR_MAX_AERA = 16; // ring image buffer IplImage **buf = 0; int last = 0; int nFrmnum=1; // 临时图像参数 IplImage *mhi = 0; // MHI: 运动历史图像 CvFilter filter = CV_GAUSSIAN_5x5; //采用5x5的高斯滤波模板 CvConnectedComp *cur_comp, min_comp; CvConnectedComp comp; CvMemStorage *storage; CvPoint pt[4]; //检测出的感兴趣区域参数 IplImage* dst_img1=0; //定义感兴趣区域图像指针 //CvMemStorage *stor1; //CvSeq *cont1; IplImage *sub_buy=0; //IplImage* sub_buy=0; // 参数： // img – 输入视频帧 // dst – 检测结果 void update_mhi( IplImage* img, IplImage* dst, int diff_threshold ) { double timestamp = clock()/100.; // 获取当前时间 CvSize size = cvSize(img->width,img->height); // 获取当前帧的大小 int i, j, idx1, idx2; int danger_x[4]; //定义危险区域的边界顶点坐标 int danger_y[4]; int obj_x[100][4]; int obj_y[100][4]; int objArea=0; int numobj=0; //定义检测到的目标数量 double ratio1,ratio2; //int danger_x2; //int danger_y2; //int danger_x3; //int danger_y3; //int danger_x4; //int danger_y4; int danger_width=60; //定义危险区域的宽度 int danger_length=40; //定义危险区域的长度 double T_area1,T_area2,T_area3,T_area4,Sb; //定义计算不规则四边形面积的所需要的变量 double Sf[4]; double F_area1[100],F_area2[100],F_area3[100],F_area4[100],St; //定义计算目标四边形面积的所需要的变量 double Sp[100][4]; char strSaveImagename[40] = "C:\\motiondetect\\"; //!保存图片的目录名 char strTmp[20]; IplImage* silh; //定义帧间差分图像指针 IplImage* Bimg=0; //定义感兴趣区域图像指针 //uchar val; //float temp; IplImage* pyr = cvCreateImage( cvSize((size.width & -2)/2, (size.height & -2)/2), 8, 1 ); CvMemStorage *stor; CvSeq *cont;// *result, *squares; //CvSeqReader reader; double Y;//,Cr,Cb; if( !mhi || mhi->width != size.width || mhi->height != size.height ) { if( buf == 0 ) { buf = (IplImage**)malloc(N*sizeof(buf[0])); memset( buf, 0, N*sizeof(buf[0])); } for( i = 0; i < N; i++ ) { cvReleaseImage( &buf[i] ); buf[i] = cvCreateImage( size, IPL_DEPTH_8U, 1 ); cvZero( buf[i] ); } cvReleaseImage( &mhi ); mhi = cvCreateImage( size, IPL_DEPTH_32F, 1 ); cvZero( mhi ); // clear MHI at the beginning } // end of if(mhi) cvCvtColor( img, buf[last], CV_BGR2GRAY ); // convert frame to grayscale idx1 = last; idx2 = (last + 1) % N; // index of (last - (N-1))th frame last = idx2; // 做帧差 silh = buf[idx2]; cvAbsDiff( buf[idx1], buf[idx2], silh ); // 帧间做差 // 对差图像做二值化 cvThreshold( silh, silh, 30, 255, CV_THRESH_BINARY ); // and threshold it cvUpdateMotionHistory( silh, mhi, timestamp, MHI_DURATION ); // update MHI cvCvtScale( mhi, dst, 255./MHI_DURATION,(MHI_DURATION - timestamp)*255./MHI_DURATION ); cvCvtScale( mhi, dst, 255./MHI_DURATION, 0 ); // 中值滤波，消除小的噪声 cvSmooth( dst, dst, CV_MEDIAN, 3, 0, 0, 0 ); // 向下采样，去掉噪声 cvPyrDown( dst, pyr, 7 ); cvDilate( pyr, pyr, 0, 1 ); // 做膨胀操作，消除目标的不连续空洞 cvPyrUp( pyr, dst, 7 ); //=================================================================================== // 下面的程序段用来找到轮廓 // Create dynamic structure and sequence. stor = cvCreateMemStorage(0); cont = cvCreateSeq(CV_SEQ_ELTYPE_POINT, sizeof(CvSeq), sizeof(CvPoint) , stor); // 找到所有轮廓 numobj=cvFindContours( dst, stor, &cont, sizeof(CvContour), CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0)); /* for(;cont;cont = cont->h_next) { // Number point must be more than or equal to 6 (for cvFitEllipse_32f). if( cont->total < 6 ) continue; // Draw current contour. cvDrawContours(img,cont,CV_RGB(255,0,0),CV_RGB(255,0,0),0,1, 8, cvPoint(0,0)); } // end of for-loop: "cont" */ //在图像窗口中绘制一个危险区域 //======================================================================== //不规则四边形顶点坐标的初始化 danger_x[0]=40; danger_y[0]=10; danger_x[3]=100; danger_y[3]=5; danger_x[1]=danger_x[0]+danger_width; danger_y[1]=danger_y[0]+danger_length; danger_x[2]=danger_x[3]+danger_width-20; danger_y[2]=danger_y[3]+danger_length; //====================================================================== // 直接使用CONTOUR中的矩形来画轮廓 for(;cont;cont = cont->h_next) { CvRect r = ((CvContour*)cont)->rect; CvFont font; obj_x[numobj][0]=r.x; obj_y[numobj][0]=r.y; obj_x[numobj][1]=r.x; obj_y[numobj][1]=r.y; obj_x[numobj][2]=r.x; obj_y[numobj][2]=r.y; obj_x[numobj][3]=r.x; obj_y[numobj][3]=r.y; for(j=0;j<4;j++) { T_area1=TrianglArea( danger_x[j],danger_y[j],r.x+r.width,r.y, r.x,r.y); T_area2=TrianglArea( danger_x[j],danger_y[j],r.x+r.width,r.y,r.x,r.y+r.height); T_area3=TrianglArea( danger_x[j],danger_y[j],r.x,r.y+r.height,r.x+r.width,r.y+r.height); T_area4=TrianglArea( danger_x[j],danger_y[j],r.x+r.width,r.y+r.height, r.x,r.y); Sf[j]=T_area1+T_area2+T_area3+T_area4; } Sb=SquArea( r.x,r.y,r.x+r.width,r.y,r.x,r.y+r.height,r.x+r.width,r.y+r.height); //计算划定的危险区域的面积 //cvSetImageROI(img, cvRect( r.x,r.y,r.x+r.width,r.y+r.height)); //设置检测出来的感兴趣的区域 //cvShowImage("img",img); for(j=0;j<4;j++) { F_area1[numobj]=TrianglArea( danger_x[0],danger_y[0],danger_x[1],danger_y[1], obj_x[numobj][j],obj_y[numobj][j]); F_area2[numobj]=TrianglArea( danger_x[2],danger_y[2],danger_x[1],danger_y[1], obj_x[numobj][j],obj_y[numobj][j]); F_area3[numobj]=TrianglArea( danger_x[2],danger_y[2],danger_x[3],danger_y[3], obj_x[numobj][j],obj_y[numobj][j]); F_area4[numobj]=TrianglArea( danger_x[3],dange