#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;
}
霍夫圆变换代码实现
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转载自blog.csdn.net/qq_43570528/article/details/102573136
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