提出了一种新的基于前向神经网络和Hopfield反馈神经网络的边界检测法，它分别探测每个象素点是否为边界点，便于实现边界检测的并行运算。首先讨论了两层前向神经网络来增强的编码被检测象素点邻域的信息，然后利用增强和编码后的邻域图象作为Hopfield反馈神经网络的输入，Hopfield神经网络收敛时得到图象边界点。这种新的神经网络边界检测法所需的计算量比传统的Hopfield网络边界检测法少得多，并增

An edge detection method based on feed forward neural network and Hopfield neuralnetwork are proposed, the feed forward neural network is used to enhance and encode the information in the region of tested pixel, and its result is the input of Hopfield neural network which does iterative working till the network converges. The new neural network saves the computational cost and can generate edge map clearer than traditional Hopfield neural network. The whole system work sun der unsupervivsed leaning, so it is easy to train the neural networks.