OpenCV：运动模板检测

标签：opencv

<span style="font-size:14px;">#include <opencv\cv.h>
#include <opencv\highgui.h>

#include <time.h>
#include <math.h>
#include <ctype.h>
#include <stdio.h>

// 不同的跟踪参数
const double MHI_DURATION = 0.5;
const double MAX_TIME_DELTA = 0.5;
const double MIN_TIME_DELTA = 0.05;
// 用于运动检测的循环帧数，与机器速度及FPS设置有关
const int N = 2;

IplImage **buf = 0;
int last = 0;

// 临时图像
IplImage *mhi = 0; // MHI: 运动历史图像
IplImage *orient = 0; // 方向
IplImage *mask = 0; // 有效的运动掩码
IplImage *segmask = 0; // 运动分割映射
CvMemStorage* storage = 0; // 临时存储区

// parameters:
//  img - input video frame
//  dst - resultant motion picture
//  args - optional parameters
void  update_mhi( IplImage* img, IplImage* dst, int diff_threshold ){

    double timestamp = clock()/1000.; // 获取当前时间,以秒为单位
    CvSize size = cvSize(img->width,img->height); // 获取当前帧尺寸
    int i, idx1 = last, idx2;
    IplImage* silh;
    CvSeq* seq;
    CvRect comp_rect;
    double count;
    double angle;
    CvPoint center;
    double magnitude;
    CvScalar color;

    // 开始时为图像分配内存 or 帧尺寸改变时重新分配内存
    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 );
        cvReleaseImage( &orient );
        cvReleaseImage( &segmask );
        cvReleaseImage( &mask );

        mhi = cvCreateImage( size, IPL_DEPTH_32F, 1 );
        cvZero( mhi ); // clear MHI at the beginning
        orient = cvCreateImage( size, IPL_DEPTH_32F, 1 );
        segmask = cvCreateImage( size, IPL_DEPTH_32F, 1 );
        mask = cvCreateImage( size, IPL_DEPTH_8U, 1 );
    }

    cvCvtColor( img, buf[last], CV_BGR2GRAY ); //RGB帧图像格式转换为gray

    idx2 = (last + 1) % N; // index of (last - (N-1))th frame
    last = idx2;

    silh = buf[idx2];
    // 相邻两帧的差
    cvAbsDiff( buf[idx1], buf[idx2], silh );

    cvThreshold( silh, silh, diff_threshold, 1, CV_THRESH_BINARY ); // 对差图像做二值化
    cvUpdateMotionHistory( silh, mhi, timestamp, MHI_DURATION ); // 更新运动历史

    // convert MHI to blue 8u image
    // cvCvtScale的第四个参数 shift = (MHI_DURATION - timestamp)*255./MHI_DURATION
    // 控制帧差的消失速率
    cvCvtScale( mhi, mask, 255./MHI_DURATION,
                (MHI_DURATION - timestamp)*255./MHI_DURATION );

    cvZero( dst );
    cvCvtPlaneToPix(mask, 0, 0, 0, dst );  // B,G,R,0 convert to BLUE image

    // 计算运动的梯度方向以及正确的方向掩码
    // Filter size = 3
    cvCalcMotionGradient( mhi, mask, orient,
                          MAX_TIME_DELTA, MIN_TIME_DELTA, 3 );

    if( !storage )
        storage = cvCreateMemStorage(0);
    else
        cvClearMemStorage(storage);

    // 运动分割： 获得运动部件的连续序列
    seq = cvSegmentMotion( mhi, segmask, storage, timestamp, MAX_TIME_DELTA );

    for( i = 0; i < seq->total; i++ ){


        if( i < 0 ) {		// 对整幅图像操作
            comp_rect = cvRect( 0, 0, size.width, size.height );
            color = CV_RGB(255,255,255);
            magnitude = 100;  // 画线长度以及圆半径的大小控制
        }
        else {          // 第i个运动组件
            comp_rect = ((CvConnectedComp*)cvGetSeqElem( seq, i ))->rect;
            // 去掉小的部分
            if( comp_rect.width + comp_rect.height < 100 )
                continue;
            color = CV_RGB(255,0,0);
            magnitude = 30;
            //if(seq->total > 0) MessageBox(NULL,"Motion Detected",NULL,0);
        }

        // 选择组件ROI
        cvSetImageROI( silh, comp_rect );
        cvSetImageROI( mhi, comp_rect );
        cvSetImageROI( orient, comp_rect );
        cvSetImageROI( mask, comp_rect );

        // 在选择的区域内，计算运动方向
        angle = cvCalcGlobalOrientation( orient, mask, mhi, timestamp,
                                         MHI_DURATION);
        angle = 360.0 - angle;  // adjust for images with top-left origin

        // 在轮廓内计算点数
        // Norm(L1) = 所有像素值的和
        count = cvNorm( silh, 0, CV_L1, 0 );

        cvResetImageROI( mhi );
        cvResetImageROI( orient );
        cvResetImageROI( mask );
        cvResetImageROI( silh );

        // 检查小运动的情形
        if( count < comp_rect.width*comp_rect.height * 0.05 )  //  像素的5%
            continue;

        // 画一个带箭头的记录以表示方向
        center = cvPoint( (comp_rect.x + comp_rect.width/2),
                          (comp_rect.y + comp_rect.height/2) );

        cvCircle( dst, center, cvRound(magnitude*1.2), color, 3, CV_AA, 0 );
        cvLine( dst, center, cvPoint( cvRound( center.x +
                                               magnitude*cos(angle*CV_PI/180)),
                                      cvRound( center.y - magnitude*sin(angle*CV_PI/180))),
                color, 3, CV_AA, 0 );
    }
}

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 );
    else if( argc == 2 )
        capture = cvCaptureFromAVI( argv[1] );

    if( capture ){

        cvNamedWindow( "Motion", 1 );
        for(;;){

            IplImage* image;
            if( !cvGrabFrame( capture ))
                break;
            image = cvRetrieveFrame( capture );

            if( image ){

                if( !motion ){

                    motion = cvCreateImage( cvSize(image->width,image->height),
                                            8, 3 );
                    cvZero( motion );
                    motion->origin = image->origin;
                }
            }

            update_mhi( image, motion, 60 );
            cvShowImage( "Motion", motion );

            if( cvWaitKey(10) >= 0 )
                break;
        }
        cvReleaseCapture( &capture );
        cvDestroyWindow( "Motion" );
    }

    return 0;
}</span>

运行结果截图：

OpenCV：运动模板检测

标签：opencv

原文地址：http://blog.csdn.net/u010002704/article/details/43734803