Ant colony search for edge detection

A novel edge detection algorithm based on ant colony optimization and heuristic search is presented. It firstly uses traditional gradient based detector to get the possible edge points. Then a heuristic ant colony search(HACS) algorithm is applied to search the possible edge points repeatedly. In each cycle, pheromones on the traversed route of each ant are updated proportional to the length of the route, and the transition routes converge on real edges progressively based on the pheromone updating rule. At last, real edges can be extracted according to the intensity of pheromones. Compared with traditional ant colony algorithms, the proposed method uses heuristic information to guide the searching process of the ants, which enhances the intention of the search, and improves the efficiency of the algorithm. Experimental results on noise images show that our method can extract real edges effectively, which keeps the edge details and suppresses the noise at the same time.