inRange函数
- void inRange(InputArray src, InputArray lowerb, InputArray upperb, OutputArray dst);
src:输入图像;
lowerb:下边界数组,阈值下限;
upperb:上边界数组,阈值上限;
dst:输出图像;
颜色范围如图:
示例:
捕获摄像头中的黄色方块
- #include<opencv2/opencv.hpp>
- using namespace cv;
- int main()
- {
- VideoCapture capture;
- capture.open(0);
- if(!capture.isOpened())
- {
- printf("can not open video file \n");
- return -1;
- }
- Mat frame, dst;
- Mat kernel;
- //开操作处理
- kernel = getStructuringElement(MORPH_RECT, Size(5, 5));
- namedWindow("input", CV_WINDOW_AUTOSIZE);
- namedWindow("output", CV_WINDOW_AUTOSIZE);
- std::vector<std::vector<Point>> contours;
- std::vector<Vec4i> hireachy;
- Rect rect;
- Point2f center;
- float radius=20;
- while (capture.read(frame))
- {
- //blur(frame, dst, Size(5,5));
- inRange(frame, Scalar(0,80,80), Scalar(50,255,255), dst);
- //开操作
- morphologyEx(dst,dst,MORPH_OPEN,kernel);
- //获取边界
- findContours(dst, contours, hireachy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point(0,0));
- //框选面积最大的边界
- if (contours.size() > 0)
- {
- double maxArea=0;
- for (int i = 0; i < contours.size(); i++)
- {
- double area = contourArea(contours[static_cast<int>(i)]);
- if (area > maxArea)
- {
- maxArea = area;
- rect = boundingRect(contours[static_cast<int>(i)]);
- minEnclosingCircle(contours[static_cast<int>(i)], center, radius);
- }
- }
- }
- //矩形框
- //rectangle(frame,rect, Scalar(0,255,0),2);
- //圆形框
- circle(frame, Point(center.x,center.y), (int)radius, Scalar(0,255,0), 2);
- imshow("input", frame);
- imshow("output", dst);
- waitKey(100);
- }
- capture.release();
- return 0;
- }
关于颜色范围的选取:
有朋友问颜色范围的事,比如我们选择某个偏红色的范围,如色环图中这个区间即BGR(0,128,255)到BGR(255,0,213);则B、G、R这三个通道的范围分别为0-255,0-128,213-255。因此阈值下限lowerb=Scalar(0,0,213),阈值上限upperb=Scalar(255,128,255)。
以上这篇opencv3/C++基于颜色的目标跟踪方式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我们。
原文链接:https://blog.csdn.net/akadiao/article/details/78881026