【摘要】 多字体特大字符集字符识别是当前OCR技术研究的热点之一。本文利用一组在抗干扰和描述字符拓扑结构方面具有互补性的特征 ,其于SupportVector技术和可增长自组织神经网络模型 ,建立一种识别系统来处理该问题。其中包括一个利用SupprtVector技术建立的OptimalMargin语言分类器 ,一个以可增长自组织神经网的粗分类器 ,结合统计和结构两种识别方法的三级汉字分类器 ,最后给出良好的实验结果 ,从而得到该识别系统为解决上述问题的有效方法之一的结论更多还原

【Abstract】 Recognition of multi font characters becomes favorable research area in OCR by now.In this paper,based on Support Vector techniques and SOFM neural network,by use of a grorp of features that are complementary in their description of geometrical and topological structure of character,we have proposed a recognition system.It include an Optimal Margin lingual classifier based on Support Vector techniques,and a three step Chinese character classifier based on growing self organizing neural network.This system adopts both of statistical template matching and structure analysis methods.At the end,following the experimental data,a conclusion is made that this system is feasible and effective.更多还原