<title>Hybrid neural networks for gray image recognition</title>

Abstract

In this paper, a new hybrid neural networks model for gray- level image recognition is presented. By the image segmentation based on the vector quantization which is carried out by Kohonen's self-organizing feature map neural networks, the gray-level image can be mapped into an Hopfield network, each neuron has several states. The performance of this model is compared with that of the traditional model. It is concluded that the new one not only has a smaller number of neurons and interconnections, but also has better error correction capabilities.