Max-Min Ant Colony Optimization Method for Edge Detection Exploiting a New Heuristic Information Function

Edge detection is a substantial operation in machine vision and image processing. Recently, many ant colony optimization (ACO) algorithms have been exploited for a wide range of optimization problem such as edge detection. In this study, we apply the max-min ant colony optimization (MMACO) method to detect the image edges. Moreover, we propose a new heuristic information function (HIF) namely group based heuristic information function (GBHIF) to determine the nodes which ants visit around their place. Our proposed HIF exploits the difference between the intensity of two groups of nodes instead of two single one. In the simulation result section we show that the robustness of proposed edge detection algorithm is more than that of the previous algorithms.