Edge Detection Based on Stack Filter and Hopfield Neural Network
基于堆栈滤波器和Hopfield神经网络的边界检测法

A new kind of edge detection method based on stack filter and Hopfield neural network is proposed in this paper.First, the stack filter with smaller filtering window size is used to optimally estimate the gradient of gray scale for each pixels of the tested image. Then, weight vector of Hopfield neural network is determined by those optimal estimated values. Finally, converged Hopfield neural network outputs the image edges. Contrast to the stack filter based edge detection. the proposed method gainis higher speed, uses less memory for optimal training of stack filter. Also contrast to the Hopfield neural network based edge detection, the proposed method havs stronger abilities of reducing the effects of noise with different distributions, and can obtain much better edges.