Neural edge detector - A good mimic of conventional one yet robuster against noise

Abstract

This paper describes a new edge detector using a multilayer neural network, called a neural edge detector (NED), and its capacity for edge detection against noise. The NED is a supervised edge detector: The NED acquires the function of a desired edge detector through training. The experiments to acquire the functions of the conventional edge detectors were performed. The experimental results have demonstrated that the NED is a good mimic for the conventional edge detectors, moreover robuster against noise: The NED can detect the similar edges to those detected by the conventional edge detector; the NED is robuster against noise than the original one is. © Springer-Verlag Berlin Heidelberg 2001.