An edge detection method based on Ant Colony System for medical images

Abstract

Edge detection plays a prominent role in the medical field, computer vision and image processing. Particularly in the medical field, it serves as a essential technique to identify disruptions, irregularities, edges, and other significant features. Ant colony optimization is nature inspired metaheuristic algorithm that is popularly applied to optimization problems. This article proposes a method for edge detection for medical images using a metaheuristic ant colony system algorithm. A new heuristic information function based on statistical range is proposed. Working systematically and behaving cooperatively, the artificial ant’s colony builds a binary image, which eventually results in edge detection. The proposed approach takes advantage of improving solutions using the revive operator. Experimental results exhibit the better performance of the proposed approach compare with existing method in terms of output image and effectiveness.