计算机工程与应用Issue(23)：189-193,5.DOI:10.3778/j.issn.1002-8331.1212-0250
基于FSVM脱机手写体汉字分类识别研究
WANG Jianping Classified identification of off-line handwritten Chinese characters recognition based on FSVM
摘要
Abstract
Considering the features of off-line handwritten Chinese characters, this paper presents a course classification method based on FSVM(Fuzzy Support Vector Machine). According to pixel density characteristics of wavelet decomposition, writer makes coarse classification on Chinese characters by using FSVM. On extracting peripheral features through fine classification and recognition, together with wavelet multi-grid characteristics, this paper relatively succeeds to do fine recognition by one-against-all method. The emulation test shows that the new method has a high recognition rate.关键词
脱机手写体汉字/模糊支持向量机/像素密度/小波Key words
off-line handwritten Chinese characters/Fuzzy Support Vector Machine(FSVM)/pixel density/wavelet分类
信息技术与安全科学引用本文复制引用
朱程辉,甘恒,王建平..基于FSVM脱机手写体汉字分类识别研究[J].计算机工程与应用,2014,(23):189-193,5.基金项目
国家实验教学示范中心项目（No.411101）。 （）
