opencv3/C++关于移动对象的轮廓的跟踪详解分享！

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;  }

以上这篇opencv3/C++关于移动对象的轮廓的跟踪详解就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持<计算机技术网(www.ctvol.com)!!>。

—-想了解opencv3/C++关于移动对象的轮廓的跟踪详解分享！全部内容且更多的C语言教程关注<计算机技术网(www.ctvol.com)!!>