求取圆形区域内的平均灰度值

#include <cmath>
#include <opencv2/opencv.hpp>
using namespace cv;
using namespace std;

const int kvalue = 15;//双边滤波邻域大小
const double PI = 3.14;//圆周率

int graylevel(Mat image, Mat dst, Point cen, int r)//求取圆形区域内的平均灰度值
{
	int graysum = 0, n = 0;

	for(int i = (cen.y - r); i <= (cen.y + r); ++i)//访问矩形框内的像素值
	{
		uchar* data = image.ptr<uchar>(i);
		for(int j = (cen.x - r); j <= (cen.x + r); ++j)
		{
			double d = (i-cen.y)*(i-cen.y) + (j-cen.x)*(j-cen.x);
			if(d < r*r)
			{
				++n;
				graysum += (int)data[j];
			}
		}
	}

	for(int i = (cen.y - r); i <= (cen.y + r); ++i)//画出圆，圆内像素值为平均灰度值
	{
		uchar* temp = dst.ptr<uchar>(i);
		for(int j = (cen.x - r); j <= (cen.x + r); ++j)
		{
			double d = (i-cen.y)*(i-cen.y) + (j-cen.x)*(j-cen.x);
			if(d < r*r)
			{
				temp[j] = (int)(graysum / n);
			}
		}
	}

	return(graysum / n);
}

int main()
{
	Mat src_color = imread("1.png");//读取原彩色图
	imshow("原图-彩色", src_color);

	Mat src_gray;//彩色图像转化成灰度图
	cvtColor(src_color, src_gray, COLOR_BGR2GRAY);
	imshow("原图-灰度", src_gray);
	//imwrite("src_gray.png", src_gray);

	//声明一个单通道图像，像素值全为0，用来将霍夫变换检测出的圆画在上面
	Mat dst(src_gray.size(), src_gray.type());
	dst = Scalar::all(0);

	Mat bf;//对灰度图像进行双边滤波
	bilateralFilter(src_gray, bf, kvalue, kvalue*2, kvalue/2);
	//imshow("灰度双边滤波处理", bf);
	//imwrite("src_bf.png", bf);

	vector<Vec3f> circles;//声明一个向量，保存检测出的圆的圆心坐标和半径
	HoughCircles(bf, circles, CV_HOUGH_GRADIENT, 1.5, 20, 130, 38, 10, 50);//霍夫变换检测圆

	std::vector<int> v;//保存圆心的横坐标减纵坐标的绝对值，用于区分两排灯
	cout << "x=\ty=\tr=\ts=\tg=" << endl;

	for(size_t i = 0; i < circles.size(); i++)//把霍夫变换检测出的圆画出来
	{
		Point center(cvRound(circles[i][0]), cvRound(circles[i][1]));
		int radius = cvRound(circles[i][2]);

		double s = 0;//计算圆的面积
		s = PI * radius * radius;

		int average = 0;
		average = graylevel(bf, dst, center, radius);//计算平均灰度，并画出圆

		circle( dst, center, 2, Scalar(255), -1, 8, 0 );//画出圆心
		circle( dst, center, radius, Scalar(255), 1, 8, 0 );//画出圆的轮廓

		v.push_back(abs(center.x-center.y));//存储圆心的横坐标减纵坐标的绝对值，用于区分两排灯

		cout << center.x << "\t" << center.y << "\t" << radius << "\t" << s << "\t" << average << endl;//在控制台输出圆心坐标和半径
	}

	sort(v.begin(), v.end());//从小到大排序

	std::vector<Point> points1, points2;//声明点向量，分别存储两排灯的圆心坐标

	for (size_t i = 0; i < circles.size(); i++)//用来区分两排灯
	{
		Point center(cvRound(circles[i][0]), cvRound(circles[i][1]));
		if (abs(center.x-center.y) < v[12])
			points1.push_back(Point(center.x, center.y));//存储从左上到右下那排灯的圆心坐标
		else
			points2.push_back(Point(center.x, center.y));//存储从左下到右上那排灯的圆心坐标
	}

	cv::Vec4f line1, line2;//拟合直线
	fitLine(Mat(points1), line1, CV_DIST_L2, 0, 0.01, 0.01);
	fitLine(Mat(points2), line2, CV_DIST_L2, 0, 0.01, 0.01);

	int x01 = (int)line1[2];
	int y01 = (int)line1[3];
	int x11 = (int)(x01 + 300*line1[0]);
	int y11 = (int)(y01 + 300*line1[1]);
	int x21 = (int)(x01 - 300*line1[0]);
	int y21 = (int)(y01 - 300*line1[1]);	

	int x02 = (int)line2[2];
	int y02 = (int)line2[3];
	int x12 = (int)(x02 + 300*line2[0]);
	int y12 = (int)(y02 + 300*line2[1]);
	int x22 = (int)(x02 - 300*line2[0]);
	int y22 = (int)(y02 - 300*line2[1]);	

	cv::line(dst, Point(x11, y11), Point(x21, y21), Scalar(255), 1);//画出直线
	cv::line(dst, Point(x12, y12), Point(x22, y22), Scalar(255), 1);

	imshow("特征提取", dst);
	imwrite("chuli.png", dst);

	waitKey();
}