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    opencv3/C++关于移动对象的轮廓的跟踪详解

    栏目:Linux/apache问题 时间:2019-12-11 22:29

    使用opencv提供的背景去除算法(KNN或高斯混合模型GMM)去除背景,然后将获取的目标二值化后通过筛选目标轮廓获得目标位置。

    #include<opencv2/opencv.hpp>
    using namespace cv;
    //基于移动对象的轮廓的跟踪
    int main()
    {
      Mat frame;
      bool flag = true;
      VideoCapture capture;
      capture.open(0);
      if (!capture.isOpened())
      {
        printf("can not open ......\n");
        return -1;
      }
      namedWindow("mask", WINDOW_AUTOSIZE);
      namedWindow("output", WINDOW_AUTOSIZE); 
      Ptr<BackgroundSubtractor> pKNN = createBackgroundSubtractorKNN();
      //Ptr<BackgroundSubtractor> pMOG2 = createBackgroundSubtractorMOG2();
      while (capture.read(frame))
      {
        Mat KNNMask;
        std::vector<std::vector<Point>>contours;
        pKNN->apply(frame, KNNMask);
        //(*pMOG2).apply(frame, mogMask);
        threshold(KNNMask, KNNMask, 100, 255, THRESH_BINARY);
        Mat kernel = getStructuringElement(MORPH_RECT, Size(3, 3));
        morphologyEx(KNNMask, KNNMask, MORPH_OPEN, kernel, Point(-1,-1));
        findContours(KNNMask, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point(0,0));
        for (int i = 0; i < contours.size(); i++)
        {
          //轮廓面积
          double area = contourArea(contours[i]);
          //轮廓外接矩阵
          Rect rect = boundingRect(contours[i]);
          if (area < 500 || rect.width < 50 || rect.height < 50) continue;
          rectangle(frame, rect, Scalar(0,255,255),2);
          putText(frame, "Target", Point(rect.x, rect.y), CV_FONT_NORMAL, FONT_HERSHEY_PLAIN, Scalar(0,255,0),2,8);
        }
        imshow("mask",KNNMask);
        imshow("output",frame);
        waitKey(1);
      }
      return 0;
    }

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