opencv基于轮廓寻找的视频流运动检测

#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;

}