#include "stdafx.h" #include <iostream> #include <opencv2/core/core.hpp> #include <opencv/cv.hpp> #include <opencv2/highgui/highgui.hpp> #include <time.h> #include <math.h> #include <ctype.h> #include <stdio.h> #include <string.h> #include<windows.h> #include <mmsystem.h> //跟踪参数 const double MHI_DURATION = 0.5;//最大跟踪时间 const double MAX_TIME_DELTA = 0.5; const double MIN_TIME_DELTA = 0.05; const int N = 3; const int CONTOUR_MAX_AERA = 100;//矩形面积 IplImage **buf = 0; int last = 0; int flag; IplImage *mhi = 0; // MHI: motion history image CvConnectedComp *cur_comp, min_comp; CvConnectedComp comp; CvMemStorage *storage; CvPoint pt[4]; // img – 输入视频帧 // dst – 检测结果 using namespace cv; using namespace std; Mat src; Mat src_gray; int thresh = 30; int max_thresh = 255; void update_mhi(IplImage* img, IplImage* dst, int diff_threshold) { double timestamp = clock() / 100.; //获取当前时间 CvSize size = cvSize(img->width, img->height); int i, idx1, idx2; IplImage* silh; IplImage* pyr = cvCreateImage(cvSize((size.width & -2) / 2, (size.height & -2) / 2), 8, 1); CvMemStorage *stor; CvSeq *cont; if (!mhi || mhi->width != size.width || mhi->height != size.height) { if (buf == 0) { buf = (IplImage**)malloc(N*sizeof(buf[0]));//动态内存分配 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); mhi = cvCreateImage(size, IPL_DEPTH_32F, 1); cvZero(mhi); } cvCvtColor(img, buf[last], CV_BGR2GRAY); //rgb->gray idx1 = last; idx2 = (last + 1) % N; last = idx2; // 做帧差 silh = buf[idx2]; cvAbsDiff(buf[idx1], buf[idx2], silh); //两帧差异 // 对差图像做二值化 cvThreshold(silh, silh, 30, 255, CV_THRESH_BINARY); //src(x,y)>threshold ,dst(x,y) = max_value; 否则,dst（x,y）=0; cvUpdateMotionHistory(silh, mhi, timestamp, MHI_DURATION); //更新像素点的运动历史 cvCvtScale(mhi, dst, 255. / MHI_DURATION, (MHI_DURATION - timestamp)*255. / MHI_DURATION);//timestamp是时间戳;MHI_DURATION，获得的是当前时间 cvCvtScale(mhi, dst, 255. / MHI_DURATION, 0); // 中值滤波，消除小的噪声 cvSmooth(dst, dst, CV_MEDIAN, 3, 0, 0, 0); // 向下采样，去掉噪声 cvPyrDown(dst, pyr, 7); cvDilate(pyr, pyr, 0, 1); // 做膨胀操作，消除目标的不连续空洞 cvPyrUp(pyr, dst, 7); // vector<vector<Point> > contours; vector<Vec4i> hierarchy; Mat canny_output(dst); // 找到所有轮廓 findContours( canny_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) ); //计算轮廓矩 vector<Moments> mu(contours.size() ); for( int i = 0; i < contours.size(); i++ ) { mu[i] = moments( contours[i], false ); } //计算轮廓的质心 vector<Point2f> mc( contours.size() ); for( int i = 0; i < contours.size(); i++ ) { mc[i] = Point2d( mu[i].m10/mu[i].m00 , mu[i].m01/mu[i].m00 ); } // 直接使用CONTOUR中的矩形来画轮廓 int order = 1; Mat drawing = Mat::zeros( canny_output.size(), CV_8UC3 ); for( int i = 0; i< contours.size(); i++ ) { Scalar color = Scalar( 255, 0, 0); double area = mu[i].m00;//面积 Rect ret1 = boundingRect(Mat(contours[i])); //获取目标序列号放置位置 if(area > 50) //剔除小面积轮廓 { drawContours( drawing, contours, i, color, 2, 8, hierarchy, 0, Point() ); circle( drawing, mc[i], 5, Scalar( 0, 0, 255), -1, 8, 0 ); rectangle(drawing, boundingRect(contours.at(i)), cvScalar(0,255,0)); char tam[100]; sprintf(tam, "(%0.0f,%0.0f)",mc[i].x,mc[i].y); putText(drawing, tam, Point(mc[i].x, mc[i].y), FONT_HERSHEY_SIMPLEX, 0.4, cvScalar(255,0,255),1); char tam1[100]; sprintf(tam1, "%d",order++); putText(drawing, tam1, Point(ret1.x+ret1.width, ret1.y+ret1.height), FONT_HERSHEY_SIMPLEX, 0.4, cvScalar(0,255,255),1); } } namedWindow( "Contours", CV_WINDOW_AUTOSIZE ); imshow( "Contours", drawing ); moveWindow("Contours",0,0); //waitKey(0); } int main(int argc, char** argv) { IplImage* motion = 0; CvCapture* capture = 0; //视频获取结构 while (1){ //capture = cvCreateCameraCapture(0);//读摄像头视频 capture = cvCreateFileCapture("C:\\Users\\Lijunliang\\Desktop\\0.5X.avi"); //读本地视频文件 if (capture) { cvNamedWindow("Motion", 1); for (;;) { SYSTEMTIME sys;//获取当前系统时间 GetLocalTime(&sys); char* t_y = new char[128]; sprintf(t_y, ("%4.4d-%2.2d-%2.2d %2.2d:%2.2d:%2.2d"), sys.wYear, sys.wMonth, sys.wDay, sys.wHour, sys.wMinute, sys.wSecond); CvFont font; cvInitFont(&font, CV_FONT_HERSHEY_COMPLEX, 0.5, 0.5, 0, 2, 8); IplImage* image; if (!cvGrabFrame(capture)) //从摄像头或者视频文件中抓取帧 break; image = cvRetrieveFrame(capture); //取回由函数cvGrabFrame抓取的图像,返回由函数cvGrabFrame 抓取的图像的指针 if (image) { if (!motion) { motion = cvCreateImage(cvSize(image->width, image->height), 8, 1); cvZero(motion); motion->origin = image->origin; ///* 0 - 顶—左结构, 1 - 底—左结构 (Windows bitmaps 风格) */ } } update_mhi(image, motion, 6); cvPutText(image, t_y, cvPoint(10, 25), &font, CV_RGB(255, 0, 0)); //cvShowImage("Motion", image); if (cvWaitKey(10) >= 0) break; } cvReleaseCapture(&capture); //cvDestroyWindow("Motion"); } } return 0; } 主要理解Opencv运动跟踪，以及质点提取等方法探讨.
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