Gabor Filter and Rough Clustering Based Edge Detection

TL;DR

This paper presents an efficient edge detection technique combining Gabor filters and rough clustering, utilizing hysteresis thresholding to accurately identify image edges and outperform some existing methods.

Contribution

It introduces a novel combination of Gabor filtering and rough clustering for improved edge detection performance.

Findings

Effective edge detection demonstrated through comparison with existing methods

Utilizes Gabor filter smoothing and rough clustering for soft computational approach

Hysteresis thresholding enhances edge extraction accuracy

Abstract

This paper introduces an efficient edge detection method based on Gabor filter and rough clustering. The input image is smoothed by Gabor function, and the concept of rough clustering is used to focus on edge detection with soft computational approach. Hysteresis thresholding is used to get the actual output, i.e. edges of the input image. To show the effectiveness, the proposed technique is compared with some other edge detection methods.