识别带颜色的圆,首先需要先查询该颜色的HSV值,
下图部分紫色归为红色了:
比如红色:
//红色的HSV值
int low_H = 0,low_S = 123,low_V = 100;
int High_H = 5,High_S = 255,High_V = 255;
然后将图片从BGR转化成HSV,接着二值化:
cvtColor(image,src,COLOR_BGR2HSV); //从BGR-> HSV
inRange(src,Scalar(low_H,low_S,low_V),Scalar(High_H,High_S,High_V),src); //二值化
如果有噪声可以去噪(这一步可以没有):
GaussianBlur(src,src,Size(5,3 ),2,2);
接着用HoughCircles来找圆,后面的参数可以根据需要自己设置:
HoughCircles(src,circles,CV_HOUGH_GRADIENT,1,50,15,7,10,30); //找圆,最后两个参数是圆半径范围,20是最小圆半径,30是最大圆半径
HoughCircles介绍:
HoughCircles
(image,method,dp,minDist [,circles [,param1 [,param2 [,minRadius [,maxRadius]]]]])
参数: |
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完整代码:
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
#pragma comment (lib, "opencv_core2413d.lib")
#pragma comment (lib, "opencv_highgui2413d.lib")
#pragma comment (lib, "opencv_imgproc2413d.lib")
#pragma comment (lib, "opencv_video2413d.lib")
#pragma comment (lib, "opencv_features2d2413d.lib")
using namespace std;
using namespace cv;
void drawCircle(Mat &input, const vector &circles);
int main(){
Mat image, src;//加载进来的图片
vector circles;//识别出来的圆,每一行是一个圆,第一列是圆心的x坐标,第二列是圆心的y坐标,第三列是圆的半径
image = imread("D:/code/map3.png");
Mat result = imread("D:/code/map3.png");//结果图
//红色的HSV值
int low_H = 0,low_S = 123,low_V = 100;
int High_H = 5,High_S = 255,High_V = 255;
cvtColor(image, src, COLOR_BGR2HSV);//从BGR->HSV
inRange(src, Scalar(low_H, low_S, low_V), Scalar(High_H, High_S, High_V), src);//二值化
//Reduce the noise so we avoid false circle detection
GaussianBlur(src, src, Size(5, 3), 2, 2);
HoughCircles(src, circles, CV_HOUGH_GRADIENT, 1, 50, 15, 7,10,30);//找圆,最后两个参数是圆半径范围,20是最小圆半径,30是最大圆半径
drawCircle(result, circles);//画圆
namedWindow("Display window1", WINDOW_NORMAL);//展示结果
namedWindow("Display window2", WINDOW_NORMAL);
resizeWindow("Display window1", 1240, 680);
resizeWindow("Display window2", 1240, 680);
imshow("Display window1", image);
imshow("Display window2", result);
waitKey(0);
return 0;
}
void drawCircle(Mat &input, const vector &circles){
for (int i = 0; i