motiondetect.c

本程序是基于VC++和opencv开发的视频入侵检测预警程序

#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],danger_y[3],danger_x[1],danger_y[1], obj_x[numobj][j],obj_y[numobj][j]);
			  Sp[numobj][j]=T_area1+T_area2+T_area3+T_area4;
			  }
			  St=SquArea( danger_x[3],danger_y[3],danger_x[1],danger_y[1],danger_x[2],danger_y[2],danger_x[3],danger_y[3]);