An Efficient Ant Colony System for Edge Detection in Image Processing

Abstract

Edge detection is a fundamental procedure in image processing, machine vision, and computer vision. Its application area ranges from astronomy to medicine in which isolating the objects of interest in the image is of a significant importance. However, performing edge detection is a non-trivial task for which a large number of techniques have been proposed to solve it. This paper investigates the use of Ant Colony Optimization — a prominent set of optimization heuristics — to solve the edge detection problem. We propose two modified versions of the algorithm Ant Colony System (ACS) for an efficient and a noise-free edge detection.