Color Image Edge Detection using Multi-scale and Multi-directional Gabor filter

TL;DR

This paper introduces a color edge detection method using multi-scale and multi-directional Gabor filters in the CIE L*a*b* space, achieving high accuracy and noise robustness in color images.

Contribution

The novel approach combines multi-scale Gabor filtering with color space conversion and Canny detection for improved color edge detection.

Findings

Higher detection accuracy compared to existing methods

Enhanced noise robustness in edge detection

Effective in processing color images with complex textures

Abstract

In this paper, a color edge detection method is proposed where the multi-scale Gabor filter are used to obtain edges from input color images. The main advantage of the proposed method is that high edge detection accuracy is attained while maintaining good noise robustness. The proposed method consists of three aspects: First, the RGB color image is converted to CIE L*a*b* space because of its wide coloring area and uniform color distribution. Second, a set of Gabor filters are used to smooth the input images and the color edge strength maps are extracted, which are fused into a new ESM with the noise robustness and accurate edge extraction. Third, Embedding the fused ESM in the route of the Canny detector yields a noise-robust color edge detector. The results show that the proposed detector has the better experience in detection accuracy and noise-robustness.