【图像处理】sobel边缘检测_c++

sobel边缘检测_c++实现

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算法步骤：

1. 输入图像

2. x,y两个方向卷积核在图像上滑动

   Gx = f(x+1, y-1) + 2 * f(x+1, y) + f(x +1, y+1) - (f(x-1, y-1) + 2 * f(x-1, y) + f(x-1, y-1))
   Gy = f(x-1, y-1) + 2 * f(x, y-1) + f(x+1, y-1) - (f(x-1, y+1) + 2 * f(x, y+1) + f(x+1, y+1))

3. G=sqrt(Gx * Gx+Gy * Gy）

4. 输出G

代码如下：

/*created at 2019/4/14*/
#include <iostream>
#include <opencv2/opencv.hpp>

cv::Mat bgr2gray(cv::Mat src)
{
	int chans = src.channels();
	cv::Mat gray;
	if(chans > 1)
		cvtColor(src, gray, CV_BGR2GRAY);
	else
		src.copyTo(gray);
	return gray;
}

void sobel_detect(cv::Mat src, cv::Mat& dst)
{
	cv::Mat in_src = bgr2gray(src);
	int rows = src.rows, cols = src.cols;

	for(int r = 1; r < rows - 1; ++r)
		for(int c = 1; c < cols -1; ++c)
		{
			float Gx = in_src.at<uchar>(r-1,c+1) + 2*in_src.at<uchar>(r,c+1) + in_src.at<uchar>(r+1,c+1) - 
				(in_src.at<uchar>(r-1,c-1) + 2*in_src.at<uchar>(r,c-1) + in_src.at<uchar>(r+1,c-1));
			float Gy = in_src.at<uchar>(r-1,c-1) + 2*in_src.at<uchar>(r-1,c) + in_src.at<uchar>(r-1,c+1) -
				(in_src.at<uchar>(r+1,c-1) + 2*in_src.at<uchar>(r+1,c) + in_src.at<uchar>(r+1,c+1));
			float G = sqrt(Gx * Gx + Gy * Gy);
			if(G > 255)
				dst.at<uchar>(r,c) = 255;
			else
				dst.at<uchar>(r,c) = G;
		}
}
int main()
{
	cv::Mat src = cv::imread("lena.jpg");
	cv::Mat dst(src.rows, src.cols, CV_8UC1);
	sobel_detect(src, dst);
	cv::imshow("sobel.jpg", dst);
	cv::waitKey(0);
	return 0;
}

原图：

输出：