A Modified Ant Colony Based Approach to Digital Image Edge Detection

Ant Colony Optimization (ACO) is a nature inspired meta-heuristic algorithms, which can be applied to a wide range of optimization problems. In this paper we present a modified method for edge detection based on the Ant Colony Optimization. Because of disadvantages of traditional edge detection methods, ACO as a relatively new meta-heuristic approach has been used to solve the edge detection problem. The performance of proposed method is compared with traditional ant colony methods, also we have large number of experiments to find out the suitable threshold for proposed method. The experimental results clearly indicate how the ACO can extracts edges in efficient way, also we speed up the proposed method by modifying the effective parameters in speed of the problem and replacing them by optimized values. The results show that this method is faster and more efficient than other former Ant Colony-based edge detection methods