Edge detection of Malaria parasites using ant colony optimization

Abstract

Ant colony optimization (ACO) is algorithm used for optimization motivated by the natural behaviour of species of ants. In this ants retain pheromone for foraging at the ground. ACO has been originated to detect the edges of microscopic images of blood samples which are affected by malaria disease. The edge detection approach of ACO is used to maintain pheromone matrix which determines the information of edges provided at every image pixel position, based on no. of ants movement that are dispatched to be in motion on the image. Thus, changes in the intensity values of images determine the movement of the ants. The results have been taken to study an approach for Ant Colony Edge Detection method.