使用OpenCV检测和追踪车辆

源文档链接：http://blog.csdn.net/xfgryujk/article/details/61421763

完整源码GitHub

1. 使用高斯混合模型（BackgroundSubtractorMOG2）对背景建模，提取出前景
2. 使用中值滤波去掉椒盐噪声，再闭运算和开运算填充空洞
3. 使用cvBlob库追踪车辆，我稍微修改了cvBlob源码来通过编译
   

由于要对背景建模，这个方法要求背景是静止的

另外不同车辆白色区域不能连通，否则会认为是同一物体

 void processVideo(char* videoFilename)
 {
     Mat frame; // current frame
     Mat fgMaskMOG2; // fg mask fg mask generated by MOG2 method
     Mat bgImg; // background
     Ptr pMOG2 = createBackgroundSubtractorMOG2(200, 36.0, false); // MOG2 Background subtractor

     while (true)
     {
         VideoCapture capture(videoFilename);
         if (!capture.isOpened())
         {
             cerr << "Unable to open video file: " << videoFilename << endl;
             return;
         }

         int width = (int)capture.get(CV_CAP_PROP_FRAME_WIDTH);
         int height = (int)capture.get(CV_CAP_PROP_FRAME_HEIGHT);

         unique_ptrvoid(*)(IplImage*)> labelImg(cvCreateImage(cvSize(width, height), IPL_DEPTH_LABEL, 1),
             [](IplImage* p){ cvReleaseImage(&p); });
         CvBlobs blobs;
         CvTracks tracks;

         while (true)
         {
             // read input data. ESC or 'q' for quitting
             int key = waitKey(1);
             if (key == 'q' || key == 27)
                 return;
             if (!capture.read(frame))
                 break;

             // update background
             pMOG2->apply(frame, fgMaskMOG2);
             pMOG2->getBackgroundImage(bgImg);
             imshow("BG", bgImg);
             imshow("Original mask", fgMaskMOG2);

             // post process
             medianBlur(fgMaskMOG2, fgMaskMOG2, 5);
             imshow("medianBlur", fgMaskMOG2);
             morphologyEx(fgMaskMOG2, fgMaskMOG2, MORPH_CLOSE, getStructuringElement(MORPH_RECT, Size(5, 5))); // fill black holes
             morphologyEx(fgMaskMOG2, fgMaskMOG2, MORPH_OPEN, getStructuringElement(MORPH_RECT, Size(5, 5))); // fill white holes
             imshow("morphologyEx", fgMaskMOG2);

             // track
             cvLabel(&IplImage(fgMaskMOG2), labelImg.get(), blobs);
             cvFilterByArea(blobs, 64, 10000);
             cvUpdateTracks(blobs, tracks, 10, 90, 30);
             cvRenderTracks(tracks, &IplImage(frame), &IplImage(frame));

             // show
             imshow("Frame", frame);

             key = waitKey(30);
         }
     }