C++利用Opencv實現(xiàn)多個圓形檢測

更新時間：2022年08月08日 14:36:33 作者：開門大弟子

霍夫圓檢測是opencv中用來檢測圓的重要算法，簡單的說，霍夫圓檢測就是對圖像中的弧線做切線，再在切點位置做切線的垂線，然后看這些垂線能交于一點的個數(shù)，這個在方法中是自己設定的

主要是利用霍夫圓檢測、面積篩選等完成多個圓形檢測，具體代碼及結(jié)果如下。

第一部分是頭文件（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);//圖像基本信息
const Mat houghCirclePre(Mat& srcPre);//霍夫圓檢測預處理
void  houghCircle(Mat& srcPreHough);//霍夫圓檢測
const Mat RectCirclePre(Mat& srcPre);//面積篩選擬合圓的預處理
void AreaCircles(Mat& AreaInput);//面積篩選擬合圓檢測

第二部分是主函數(shù)：

#include"common.h"
Mat src;
int main()
{
    src = imread("1.jpg",1);
    if (src.empty())
    {
        cout << "圖像不存在！" << endl;
    }
    else
    {
        namedWindow("原圖", 1);
        imshow("原圖", src);
        imageBasicInformation(src);
        Mat srcPreHough = houghCirclePre(src);
        houghCircle(srcPreHough);
        Mat RectCir = RectCirclePre(src);
        AreaCircles(RectCir);
        waitKey(0);
        destroyAllWindows();
    }
    return 0；
}

第三部分為霍夫圓檢測函數(shù)（hough.cpp）

主要包括輸出圖像的基本信息函數(shù)：void imageBasicInformation(Mat& src)

霍夫圓檢測預處理函數(shù)：const Mat houghCirclePre(Mat& srcPre)

霍夫圓檢測函數(shù)：void houghCircle(Mat& srcPreHough)

#include"common.h"
Mat graySrc, srcPre;//灰度圖，霍夫檢測預處理，
Mat threshold_grayaSrc;//二值化圖
Mat erode_threshold_graySrc, dilate_threshold_graySrc;//二值化后腐蝕，二值化后膨脹
void imageBasicInformation(Mat& src)
{
    int cols = src.cols;
    int rows = src.rows;
    int channels = src.channels();
    cout << "圖像寬為：" << cols << endl;
    cout << "圖像高為：" << rows << endl;
    cout << "圖像通道數(shù)：" << 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);//濾波
    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);//膨脹
    erode(dilate_threshold_graySrc, erode_threshold_graySrc, element);//腐蝕
    houghCirclePreTime = ((double)getTickCount() - houghCirclePreTime) / getTickFrequency();
    cout << "霍夫圓預處理時間為：" << houghCirclePreTime << "秒" << endl;
    return erode_threshold_graySrc;
}
void houghCircle(Mat& srcPreHough)
{
    cout << "進入霍夫圓檢測" << endl;
    vector<Vec3f> circles;
    HoughCircles(srcPreHough, circles, HOUGH_GRADIENT, 1, 60, 1, 35, 0, 0);
    cout << "圓的個數(shù)" << 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);//畫圓心
        circle(src, center, radius, Scalar(0, 0, 255), 3, 8, 0);//畫圓
    }
    namedWindow("霍夫檢測結(jié)果", 0);
    imshow("霍夫檢測結(jié)果", src);
    imwrite("霍夫圓檢測結(jié)果.jpg", src);//保存檢測結(jié)果
}

第四部分為利用面積篩選擬合圓檢測（AreaCircle.cpp）

主要包括預處理函數(shù)：const Mat RectCirclePre(Mat& srcPre)

面積篩選擬合圓檢測函數(shù)：void AreaCircles(Mat& AreaInput)

#include"common.h"
Mat graySrcArea, thresholdGraySrc;//灰度圖像，二值化圖像
Mat dilateThresholdGraySrc, erodeThresholdGraySrc;//二值化后膨脹圖像，膨脹之后的腐蝕圖像
const Mat RectCirclePre(Mat& srcPre)
{ 
	cvtColor(srcPre, graySrcArea, COLOR_BGR2GRAY);
	GaussianBlur(graySrcArea, graySrcArea, Size(3, 3), 2, 2);
	threshold(graySrcArea, thresholdGraySrc, 100, 255, 1);//二值化，閾值要根據(jù)自己的圖像自己調(diào)整
	Mat element = getStructuringElement(MORPH_RECT, Size(15, 15));
	dilate(thresholdGraySrc, dilateThresholdGraySrc, element);//膨脹
	erode(dilateThresholdGraySrc, erodeThresholdGraySrc, element);//腐蝕
	return erodeThresholdGraySrc;
}
void AreaCircles(Mat& AreaInput)
{
	vector<vector<Point>> RectContours;
	vector<Vec4i> Hierarchy;
	findContours(AreaInput, RectContours, Hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0));
	Mat drawing = Mat::zeros(src.size(), CV_8UC3);
	for (int i = 0;i < RectContours.size();i++)
	{
		double area = contourArea(RectContours[i]);
		cout << area << endl;//輸出所有計算出來的面積，方便下一步設置閾值
		if (area > 15000 && area < 100000)//根據(jù)上一步計算的閾值設置范圍
		{
			drawContours(drawing, RectContours, i, Scalar(0, 255, 0), 2,8, Hierarchy, 0, Point());
			RotatedRect Rect = fitEllipse(RectContours[i]);
			circle(src, Rect.center, 2, Scalar(0, 255, 0), 2, 8, 0);//在原圖畫出圓心
			ellipse(src, Rect, Scalar(0, 0, 255), 2);//在原圖畫出輪廓
		}
	}
	namedWindow("面積篩選擬合圓", 0);
	imshow("面積篩選擬合圓", src);
	imwrite("面積篩選擬合圓.jpg", src);//保存檢測結(jié)果
}

結(jié)果如下（自己畫的兩個圓）：

原圖：