Edge Detection of Medical Images Using Modified Ant Colony Optimization Algorithm based on Weighted Heuristics

Abstract

Ant Colony Optimization (ACO) is nature inspired algorithm based on foraging behaviour of ants. The algorithm is based on the fact how ants deposit pheromone while searching for food. ACO generates a pheromone matrix which gives the edge information present at each pixel position of image, formed by ants dispatched on image. The movement of ants depends on local variance of image's intensity value. This paper proposes an improved method based on heuristic which assigns weight to the neighbourhood. Thus by assigning the weights or priority to the neighbouring pixels, the ant decides in which direction it can move. The method is applied on Medical images and experimental results are provided to support the superior performance of the proposed approach and the existing method.