A Hybrid Approach to Edge Detection using Ant Colony Optimization and Fuzzy Logic

Edge detection aims to mark sharp intensity changes in an image and is a basis for a large number of image analysis and machine vision applications. Ant colony optimization is an evolutionary optimization algorithm which is inspired by food searching behaviour of ant species. An edge detection algorithm that combines an ant colony optimization and fuzzy logic is presented in this paper. The heuristics information for movement of ants is decided by using fuzzy logic. Experimental results are provided to demonstrate the superior performance of proposed method.