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服务器之家。
原文链接:https://blog.csdn.net/akadiao/article/details/78967676