基于模糊规则和相似测量的手写汉字预分类法  

Preclassification for Handwritten Chinese Character Based on Fuzzy Rules and Similarity Measure

作　　者：卢达[1] 陈琦玮[1] 谢铭培[2] 

机构地区：[1]常熟理工学院,江苏常熟215500 [2]复旦大学计算机科学系,上海200433

出　　处：《计算机工程与应用》2005年第25期75-77,84,共4页Computer Engineering and Applications

基　　金：江苏省教育厅自然科学研究项目(批准号:02KJD540001)

摘　　要：文章提出了一种手写汉字预分类的新方法,该方法分两步进行,首先提取笔划密度特征并用模糊规则产生四个预分类组;然后通过模糊逻辑处理将各组字符分别转换成基于非线性加权函数的模糊样板并通过基于模糊相似测量的匹配算法、相似性测量样板的分级分类进行预分类。测试结果表明,该方法效果良好,预分类正确率达到98.17%。A method of character preclassification for handwritten Chinese character recognition is proposed in this paper.This method includes two stages：In stage I,extracting stroke density features and using fuzzy rules to create four preclassification groups.In stage II,transforming the characters in each group into fuzzy prototypes based on a nonlinear weighted similarity function with fuzzy logic approach,then using matching algorithm and hierachic classification of fuzzy prototypes of similarity measurement for character preclassification.The experiment shows this method is effective and the characters of the testing set can be distributed into correct preclassification classes at a rate of 98.17%.

关 键 词：手写汉字预分类 模糊规则分类 模糊相似测量 匹配算法 分级分类 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]