A new algorithm for edge detection by hybrid differential evolution algorithm

In this paper, a new algorithm for edge detection was proposed. This method inspired by A. Bastürk´s thoughts was formed, who proposed efficient edge detection using one neighbor CNN cloning template optimized by differential evolutionary algorithm. In order to consider interaction of more cells, and overcome solution´s precocious phenomena, this paper extend one neighbor to two neighbors, and adopt hybrid differential evolutionary algorithm with a disturbance mutation operator optimizing two neighbors CNN cloning template. Through the general test images, simulation experiments indicate that the proposed method comparing with traditional edge detection methods has obvious advantage.