OpenCV学习——基于轮廓寻找的视频流运动检测

原文出处：http://blog.csdn.net/gnuhpc/article/details/4286183

#include "cv.h"#include "highgui.h"#include <time.h>#include <math.h>#include <ctype.h>#include <stdio.h>#include <string.h>// various tracking parameters (in seconds) //跟踪的参数（单位为秒）const double MHI_DURATION = 0.5;//0.5s为运动跟踪的最大持续时间const double MAX_TIME_DELTA = 0.5;const double MIN_TIME_DELTA = 0.05;const int N = 3;//const int CONTOUR_MAX_AERA = 1000;// ring image buffer 圈出图像缓冲IplImage **buf = 0;//指针的指针int last = 0;// temporary images临时图像IplImage *mhi = 0; // MHI: motion history imageCvFilter filter = CV_GAUSSIAN_5x5;CvConnectedComp *cur_comp, min_comp;CvConnectedComp comp;CvMemStorage *storage;CvPoint pt[4];//  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.; // get current time in seconds 时间戳    CvSize size = cvSize(img->width,img->height);    // get current frame size，得到当前帧的尺寸    int i, idx1, idx2;    IplImage* silh;    IplImage* pyr = cvCreateImage( cvSize((size.width & -2)/2, (size.height & -2)/2), 8, 1 );    CvMemStorage *stor;    CvSeq *cont;    /*先进行数据的初始化*/    if( !mhi || mhi->width != size.width || mhi->height != size.height )    {        if( buf == 0 ) //若尚没有初始化则分配内存给他        {            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] );// clear Buffer Frame at the beginning        }        cvReleaseImage( &mhi );        mhi = cvCreateImage( size, IPL_DEPTH_32F, 1 );        cvZero( mhi ); // clear MHI at the beginning    } // end of if(mhi)    /*将当前要处理的帧转化为灰度放到buffer的最后一帧中*/    cvCvtColor( img, buf[last], CV_BGR2GRAY ); // convert frame to grayscale    /*设定帧的序号*/    /*    last---->idx1     ^     |     |     |    idx2<-----(last+1)%3    */        idx1 = last;    idx2 = (last + 1) % N; // index of (last - (N-1))th frame    last = idx2;    // 做帧差    silh = buf[idx2];//差值的指向idx2 |idx2-idx1|-->idx2(<-silh)    cvAbsDiff( buf[idx1], buf[idx2], silh ); // get difference between frames        // 对差图像做二值化    cvThreshold( silh, silh, 30, 255, CV_THRESH_BINARY ); //threshold it,二值化        cvUpdateMotionHistory( silh, mhi, timestamp, MHI_DURATION ); // update MHI     cvConvert( mhi, dst );//将mhi转化为dst,dst=mhi           // 中值滤波，消除小的噪声    cvSmooth( dst, dst, CV_MEDIAN, 3, 0, 0, 0 );            cvPyrDown( dst, pyr, CV_GAUSSIAN_5x5 );// 向下采样，去掉噪声，图像是原图像的四分之一    cvDilate( pyr, pyr, 0, 1 );  // 做膨胀操作，消除目标的不连续空洞    cvPyrUp( pyr, dst, CV_GAUSSIAN_5x5 );// 向上采样，恢复图像，图像是原图像的四倍    //    // 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    cvFindContours( dst, stor, &cont, sizeof(CvContour),                    CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0));    // 直接使用CONTOUR中的矩形来画轮廓    for(;cont;cont = cont->h_next)    {              CvRect r = ((CvContour*)cont)->rect;              if(r.height * r.width > CONTOUR_MAX_AERA) // 面积小的方形抛弃掉              {                  cvRectangle( img, cvPoint(r.x,r.y),                          cvPoint(r.x + r.width, r.y + r.height),                          CV_RGB(255,0,0), 1, CV_AA,0);              }    }    // free memory    cvReleaseMemStorage(&stor);    cvReleaseImage( &pyr );}int main(int argc, char** argv){    IplImage* motion = 0;    CvCapture* capture = 0;        if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0])))        capture = cvCaptureFromCAM( argc == 2 ? argv[1][0] - '0' : 0 );//摄像头为视频来源    else if( argc == 2 )        capture = cvCaptureFromAVI( argv[1] );//AVI为视频来源    if( capture )    {        cvNamedWindow( "Motion", 1 );//建立窗口        for(;;)        {            IplImage* image;            if( !cvGrabFrame( capture ))//捕捉一桢                break;            image = cvRetrieveFrame( capture );//取出这个帧            if( image )//若取到则判断motion是否为空            {                if( !motion )                {                    motion = cvCreateImage( cvSize(image->width,image->height), 8, 1 );                    //创建motion帧，八位，一通道                    cvZero( motion );                    //零填充motion                    motion->origin = image->origin;                    //内存存储的顺序和取出的帧相同                }            }            update_mhi( image, motion, 60 );//更新历史图像            cvShowImage( "Motion", image );//显示处理过的图像            if( cvWaitKey(10) >= 0 )//10ms中按任意键退出                break;        }        cvReleaseCapture( &capture );//释放设备        cvDestroyWindow( "Motion" );//销毁窗口    }    return 0;}