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IMCS/Publications/CSJM/Issues/CSJM v.23, n.3 (69), 2015/

Edge detection in digital images using Ant Colony Optimization

Authors: Marjan Kuchaki Rafsanjani, Zahra Asghari Varzaneh
Keywords: Ant Colony Optimization (ACO), Digital image processing, Edge detection, Noisy images

Abstract

Ant Colony Optimization (ACO) is an optimization algorithm inspired by the behavior of real ant colonies to approximate the solutions of difficult optimization problems. In this paper, ACO is introduced to tackle the image edge detection problem. The proposed approach is based on the distribution of ants on an image; ants try to find possible edges by using a state transition function. Experimental results show that the proposed method compared to standard edge detectors is less sensitive to Gaussian noise and gives finer details and thinner edges when compared to earlier ant-based approaches.

Department of Computer Science,
Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran
E-mail: ,

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