Opencv检测多个圆形(霍夫圆检测，轮廓面积筛选)

主要是利用霍夫圆检测、面积筛选等完成多个圆形检测，具体代码及结果如下。

第一部分是头文件（common.h）：

#pragma once
#include<opencv2/opencv.hpp>
#include<opencv2/highgui.hpp>
#include<iostream>

using namespace std;
using namespace cv;

extern Mat src;
void imageBasicInformation(Mat& src);//图像基本信息

const Mat houghCirclePre(Mat& srcPre);//霍夫圆检测预处理
void  houghCircle(Mat& srcPreHough);//霍夫圆检测
const Mat RectCirclePre(Mat& srcPre);//面积筛选拟合圆的预处理
void AreaCircles(Mat& AreaInput);//面积筛选拟合圆检测

第二部分是主函数：

#include"common.h"
Mat src;
int main()
{
    src = imread("1.jpg",1);
    if (src.empty())
    {
        cout << "图像不存在！" << endl;
    }
    else
    {
        namedWindow("原图", 1);
        imshow("原图", src);
        imageBasicInformation(src);
        Mat srcPreHough = houghCirclePre(src);
        houghCircle(srcPreHough);

        Mat RectCir = RectCirclePre(src);
        AreaCircles(RectCir);
        waitKey(0);
        destroyAllWindows();
    }
    return 0；
}

第三部分为霍夫圆检测函数（hough.cpp）

主要包括输出图像的基本信息函数：void imageBasicInformation(Mat& src)
霍夫圆检测预处理函数：const Mat houghCirclePre(Mat& srcPre)
霍夫圆检测函数：void houghCircle(Mat& srcPreHough)

#include"common.h"

Mat graySrc, srcPre;//灰度图，霍夫检测预处理，
Mat threshold_grayaSrc;//二值化图
Mat erode_threshold_graySrc, dilate_threshold_graySrc;//二值化后腐蚀，二值化后膨胀

void imageBasicInformation(Mat& src)
{
    int cols = src.cols;
    int rows = src.rows;
    int channels = src.channels();
    cout << "图像宽为：" << cols << endl;
    cout << "图像高为：" << rows << endl;
    cout << "图像通道数：" << channels << endl;
}

const Mat houghCirclePre(Mat& srcPre)
{
    double houghCirclePreTime = static_cast<double>(getTickCount());

    cvtColor(srcPre, graySrc, COLOR_BGR2GRAY);
    GaussianBlur(graySrc, graySrc, Size(3, 3), 2, 2);//滤波
    threshold(graySrc, threshold_grayaSrc, 150, 255, 1);//二值化

    Mat element = getStructuringElement(MORPH_RECT, Size(15, 15));
    dilate(threshold_grayaSrc, dilate_threshold_graySrc, element);//膨胀
    erode(dilate_threshold_graySrc, erode_threshold_graySrc, element);//腐蚀
    houghCirclePreTime = ((double)getTickCount() - houghCirclePreTime) / getTickFrequency();
    cout << "霍夫圆预处理时间为：" << houghCirclePreTime << "秒" << endl;
    return erode_threshold_graySrc;
}

void houghCircle(Mat& srcPreHough)
{
    cout << "进入霍夫圆检测" << endl;
    vector<Vec3f> circles;
    HoughCircles(srcPreHough, circles, HOUGH_GRADIENT, 1, 60, 1, 35, 0, 0);
    cout << "圆的个数" << circles.size() << endl;
    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(src, center, 3, Scalar(0, 255, 0), -1, 8, 0);//画圆心
        circle(src, center, radius, Scalar(0, 0, 255), 3, 8, 0);//画圆
    }
    namedWindow("霍夫检测结果", 0);
    imshow("霍夫检测结果", src);
    imwrite("霍夫圆检测结果.jpg", src);//保存检测结果
}

第四部分为利用面积筛选拟合圆检测（AreaCircle.cpp）

主要包括预处理函数：const Mat RectCirclePre(Mat& srcPre)
面积筛选拟合圆检测函数：void AreaCircles(Mat& AreaInput)

#include"common.h"

Mat graySrc, srcPre;//灰度图，霍夫检测预处理，
Mat threshold_grayaSrc;//二值化图
Mat erode_threshold_graySrc, dilate_threshold_graySrc;//二值化后腐蚀，二值化后膨胀

void imageBasicInformation(Mat& src)
{
    int cols = src.cols;
    int rows = src.rows;
    int channels = src.channels();
    cout << "图像宽为：" << cols << endl;
    cout << "图像高为：" << rows << endl;
    cout << "图像通道数：" << channels << endl;
}

const Mat houghCirclePre(Mat& srcPre)
{
    double houghCirclePreTime = static_cast<double>(getTickCount());

    cvtColor(srcPre, graySrc, COLOR_BGR2GRAY);
    GaussianBlur(graySrc, graySrc, Size(3, 3), 2, 2);//滤波
    threshold(graySrc, threshold_grayaSrc, 150, 255, 1);//二值化

    Mat element = getStructuringElement(MORPH_RECT, Size(15, 15));
    dilate(threshold_grayaSrc, dilate_threshold_graySrc, element);//膨胀
    erode(dilate_threshold_graySrc, erode_threshold_graySrc, element);//腐蚀
    houghCirclePreTime = ((double)getTickCount() - houghCirclePreTime) / getTickFrequency();
    cout << "霍夫圆预处理时间为：" << houghCirclePreTime << "秒" << endl;
    return erode_threshold_graySrc;
}

void houghCircle(Mat& srcPreHough)
{
    cout << "进入霍夫圆检测" << endl;
    vector<Vec3f> circles;
    HoughCircles(srcPreHough, circles, HOUGH_GRADIENT, 1, 60, 1, 35, 0, 0);
    cout << "圆的个数" << circles.size() << endl;
    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(src, center, 3, Scalar(0, 255, 0), -1, 8, 0);//画圆心
        circle(src, center, radius, Scalar(0, 0, 255), 3, 8, 0);//画圆
    }
    namedWindow("霍夫检测结果", 0);
    imshow("霍夫检测结果", src);
    imwrite("霍夫圆检测结果.jpg", src);//保存检测结果
}

结果如下（自己画的两个圆）：
原图：

以下为霍夫圆检测结果：

以下为面积筛选拟合圆结果：

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