Edge detection is one of the commonly used techniques in computer vision and image processing, which is used to extract the boundaries of objects in images. The Canny edge detection algorithm is a classic method that can achieve high-quality edge detection results. This article will introduce the principle of Canny algorithm and provide Matlab source code implementation.
The main steps of the Canny algorithm include Gaussian filtering, calculation of gradient amplitude and direction, non-maximum suppression and double threshold processing. Below we will introduce each step in detail step by step and give the corresponding Matlab source code.
- Gaussian filtering
Gaussian filtering is the first step of the Canny algorithm and is used to smooth the image and reduce noise. It is implemented by convolving the image with a Gaussian kernel. The following is the Matlab source code implementation:
sigma = 1.4; % 高斯核标准差
filter_size = 5; % 高斯核大小
% 生成高斯核
gaussian_filter = fspecial('gaussian', filter_siz