OpenCV实践：低对比度图像检测圆形轮廓

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前言

最近在51Halcon答疑区有找到一个检测实例：在低对比度图像中检测圆形轮廓，这里分享给大家。

问题链接：
https://www.51halcon.com/thread-4876-1-1.html

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1. 问题描述

问题提出者想要在如下图片中找到圆形轮廓：

2. OpenCV 实现步骤

主要步骤如下：

1. 读取原图并转换为灰度图；
2. 提取ROI区域；
3. 阈值分割
4. 查找轮廓并根据圆形轮廓特征（半径大小，外界矩形长宽比）过滤轮廓
5. 绘制圆形轮廓；

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3. 源码实现

#include <iostream>
#include <opencv2\imgcodecs.hpp>
#include <opencv2\core.hpp>
#include <opencv2\imgproc.hpp>
#include <opencv2\highgui.hpp>
#include <vector>

using namespace cv;

int main()
{
    
    
	std::string strImgFile = "C:\\Temp\\common\\Workspace\\Opencv\\images\\BlueROI.jpg";
	Mat mSrc = imread(strImgFile);
	CV_Assert(!mSrc.empty());

	//resize(mSrc, mSrc, Size(mSrc.cols / 2, mSrc.rows / 2));

	Mat mGray;
	cvtColor(mSrc, mGray, COLOR_BGR2GRAY);
	CV_Assert(!mGray.empty());

	imshow("gray", mGray);

	Mat mRoi;
	mGray(Rect(Point(160, 70), Point(160 + 210, 70 + 220))).copyTo(mRoi);
	CV_Assert(!mRoi.empty());

	imshow("roi", mRoi);
	
	Mat mThresh;
	double thresh = threshold(mRoi, mThresh, 30, 255, THRESH_BINARY_INV);
	std::cout << "Threshold value:" << thresh << std::endl;
	CV_Assert(!mThresh.empty());
	
	imshow("threshold", mThresh);

	/*Mat mCircleKernel = getStructuringElement(MORPH_ELLIPSE, Size(3, 3));
	Mat mMorph;
	morphologyEx(mThresh, mMorph, MORPH_DILATE, mCircleKernel);
	CV_Assert(!mMorph.empty());

	imshow("morph", mMorph);*/

	Mat mSrcCopy = mSrc.clone();
	std::vector<std::vector<Point>> contours;
	findContours(mThresh, contours, RETR_EXTERNAL, CHAIN_APPROX_NONE);

	for (int i = 0; i < contours.size(); i++)
	{
    
    
		Point2f center;
		float radius;
		minEnclosingCircle(contours[i], center, radius);

		RotatedRect rr = minAreaRect(contours[i]);
		int max = rr.size.width > rr.size.height ? rr.size.width : rr.size.height;
		int min = rr.size.height > rr.size.width ? rr.size.width : rr.size.height;

		if (radius > 10 && radius < 50 && max / min < 1.5)
		{
    
    
			//drawContours(mSrcCopy, contours, i, Scalar(0, 0, 255), 1, 8, noArray(), 2000, Point(160, 70));
			circle(mSrcCopy, Point(int(center.x + 160), int(center.y + 70)), int(radius-5), Scalar(0, 0, 255));
		}
	}

	imshow("result", mSrcCopy);


	waitKey();
	destroyAllWindows();
	return 0;
}

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4. 结果展示

总结

这里的实现比较粗糙，没有准确定位要检测的圆形轮廓，目前没有想到比较好的方法，如果有大神有好的方法，希望不吝赐教，谢谢！