双X特征下自组织竞争网络的手写字符识别

Abstract

By studying of image processing,character feature extraction and neural network including network type selection,network parameter optimization,training and adjustment,the handwritten character recognition method based on self-organizing network with double-X feature as input is proposed.First of all,the image is preprocessed including gray,binaryzation,tailoring and scaling.Second,the characters' double-X feature extraction method is utilized to extract feature information of various characters.Finally,the feature data of cha-racters is input into self-organizing network for learning and to determine the ideal network parameters after many tests,so that it can be self-organized to distinguish the character-mode.Experimental results show that this approach reduces the amount of data inputed to the network,and the interference of redundant information to network,and the complexity of network processing was considerably reduced.The network training error is small and the network misjudged rate is just about 12%.