#include "opencv2/highgui/highgui.hpp" #include "opencv2/imgproc/imgproc.hpp" #
include <opencv2/highgui/highgui_c.h> #include <iostream> #include <stdio.h> #
include <vector> using namespace cv; using namespace std; /** @function main */
int main(int argc, char** argv) { Mat src, src_gray; /// 加载图像 src = imread(
“此处填图片位置”, 1 ); if( !src.data ) { return -1; } /// 转成灰度图: cvtColor( src,
src_gray, CV_BGR2GRAY ); ///执行高斯模糊以降低噪声 GaussianBlur( src_gray, src_gray, Size(9
, 9), 2, 2 ); vector<Vec3f> circles; /// 执行霍夫圆变换 HoughCircles( src_gray, circles
, CV_HOUGH_GRADIENT, 1, src_gray.rows/8, 200, 100, 0, 0 ); // src_gray: 输入图像
(灰度图) //circles: 存储下面三个参数: x_{c}, y_{c}, r 集合的容器来表示每个检测到的圆. //
CV_HOUGH_GRADIENT: 指定检测方法. 现在OpenCV中只有霍夫梯度法 //dp = 1: 累加器图像的反比分辨率 // min_dist =
src_gray.rows/8: 检测到圆心之间的最小距离 //param_1 = 200: Canny边缘函数的高阈值 // param_2 = 100:
圆心检测阈值. // min_radius = 0: 能检测到的最小圆半径, 默认为0. // max_radius = 0: 能检测到的最大圆半径, 默认为0
/// 绘出检测到的圆: for( size_t i = 0; i < circles.size(); i++ ) { Point center(cvRound
(circles[i][0]), cvRound(circles[i][1])); int radius = cvRound(circles[i][2]);
// circle center circle( src, center, 3, Scalar(0,255,0), -1, 8, 0 ); // circle
outline circle( src, center, radius, Scalar(0,0,255), 3, 8, 0 ); } /// 显示检测到的圆:
namedWindow( "Hough Circle Transform Demo", CV_WINDOW_AUTOSIZE ); imshow(
"Hough Circle Transform Demo", src ); waitKey(0); return 0; }
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