使用OpenCV实现检测和追踪车辆

本文实例为大家分享了OpenCV实现检测和追踪车辆的具体代码，供大家参考，具体内容如下

完整源码GitHub

• 使用高斯混合模型（BackgroundSubtractorMOG2）对背景建模，提取出前景
• 使用中值滤波去掉椒盐噪声，再闭运算和开运算填充空洞
• 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<BackgroundSubtractorMOG2> 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_ptr<IplImage, void(*)(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); 
    } 
  } 
} 

以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持猪先飞。