【OpenCV学习】基于轮廓寻找的视频流运动检测

作者:gnuhpc
出处:http://www.cnblogs.com/gnuhpc/

#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 image
CvFilter 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;
} 

 

作者:gnuhpc
出处:http://www.cnblogs.com/gnuhpc/

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