智能交通系统 虚拟线圈 车流量检测 OpenCV 智能交通系统

#include "cv.h" #include "highgui.h" #include <time.h> #include <math.h> #include <ctype.h> #include <stdio.h> // 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; // 用于运动检测的循环帧数，与机器速度以及FPS设置有关 const int N = 2; // ring image buffer IplImage **buf = 0; int last = 0; // temporary images IplImage *mhi = 0; // MHI: motion history image IplImage *orient = 0; // orientation IplImage *mask = 0; // valid orientation mask IplImage *segmask = 0; // motion segmentation map CvMemStorage* storage = 0; // temporary storage // 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.; // get current time in seconds CvSize size = cvSize(img->width,img->height); // get current frame size int i, idx1 = last, idx2; IplImage* silh; CvSeq* seq; CvRect comp_rect; double count; double angle; CvPoint center; double magnitude; CvScalar color; // allocate images at the beginning or // reallocate them if the frame size is changed 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 ); // convert frame to grayscale 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 ); // get difference between frames // 对差图像做二值化 cvThreshold( silh, silh, diff_threshold, 1, CV_THRESH_BINARY ); // and threshold it cvUpdateMotionHistory( silh, mhi, timestamp, MHI_DURATION ); // update MHI // 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 －> dist : convert to BLUE image // 计算运动的梯度方向以及正确的方向掩模mask // 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 // segmask is marked motion components map. It is not used further seq = cvSegmentMotion( mhi, segmask, storage, timestamp, MAX_TIME_DELTA ); // iterate through the motion components, // One more iteration (i == -1) corresponds to the whole image (global motion) for( i = 0; i < seq->total; i++ ) { if( i < 0 ) { // case of the whole image，对整幅图像做操作 comp_rect = cvRect( 0, 0, size.width, size.height ); color = CV_RGB(255,255,255); // white color magnitude = 100; // 画线长度以及圆半径的大小控制 } else { // i-th motion component 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); // red color magnitude = 30; //if(seq->total > 0) MessageBox(NULL,"Motion Detected",NULL,0); } // select component 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) = sum of total pixel values count = cvNorm( silh, 0, CV_L1, 0 ); // The function cvResetImageROI releases image ROI cvResetImageROI( mhi ); cvResetImageROI( orient ); cvResetImageROI( mask ); cvResetImageROI( silh ); // check for the case of little motion if( count < comp_rect.width*comp_rect.height * 0.05 ) // five percent of pixel continue; // draw a clock with arrow indicating the direction 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; }