An Improved Canny Algorithm Based on Recursive Gaussian Filter and Its Application
GE Lei
MA Junxia
Abstract：Edge detection is a basic problem of computer vision and image processing,and its detection effect is inseparable from the quality of the image.However,in the process of image signal acquisition,it is inevitable that noise and other influencing factors will be mixed.Canny's algorithm has attracted a lot of attention because of its good accuracy in smoothing images and remov-ing noise.However,in the traditional Canny edge detection method,Gaussian filters are mostly based on the same direction,and the utilization of information in the edge direction is low.In order to enhance the utilization of edge information and the smoothing ef-fect of Gaussian filtering,anisotropic Gaussian filters are usually used to improve the filtering effect,but at the same time,the com-plexity of their calculations increases.To solve the above problems,an improved method for image denoising based on recursive Gaussian filter is proposed.In this method,the two-dimensional filtering of the anisotropic Gaussian filter is decomposed into two one-dimensional filters,and a forward filter is performed first,on the basis of which the backward filtering is performed,and the re-sults of each filter are updated iteratively.Experimental results show that the proposed recursive Gaussian filter not only reduces the complexity of the original algorithm,but also significantly improves the edge detection effect applied to the Canny algorithm.
Keywords：edge detectionimage denoisinganisotropyrecursive Gaussian filterone dimensional filtering
Publication Date：2025-11-20
Online Publishing Date：2026-01-28(First online date of this platform, not the publication date of the document)
Pages：6( 3208-3213 )