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我们。

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