Tibetan character recognition is a significant module of Chinese multi language information processing system, however hardly any research work has been undertaken yet.
藏文字符识别系统是中文多文种信息处理系统的重要组成部分，但至今国内外的研究基本处于空白。
This paper presented a new multi-template character recognition method based on principal component analysis(PCA).
本文提出了一种基于主元分析法（PCA）的多模板字符识别算法。
While displaying a rich ethnical and regional character, the ethnic finery is also the symbol of cultural recognition in a country with multi-ethnic groups.
民族服饰在彰显浓郁的民族和地域特色的同时，还是多民族国家文化认同的外在符号。
An algorithm for stroke corner detection based on curvature multi-calculation is proposed to extract characteristics for OLCCR (on-line handwritten Chinese character recognition).
提出一个基于多重曲率计算的角点检测算法，对联机手写汉字识别中的笔划拐点进行提取。
Proposed in this paper is a fast multi-stage classification strategy for large class sets, such as handwriting Chinese character recognition.
针对大类别集分类问题提出了一种新的快速分类方法。
In developing the multi-fonts Chinese character recognition system by structural approach, the stroke extraction is an important problem.
在实现结构分析法识别多字体印刷汉字时，笔划抽取是关键所在。
Finallly taking advantage of the trained network model as a classifier, we implemented a multi-level strategy Chinese character recognition system.
并利用训练后得到的网络作为分类器设计并实现了一种多级策略的汉字识别系统。
Finallly taking advantage of the trained network model as a classifier, we implemented a multi-level strategy Chinese character recognition system.
并利用训练后得到的网络作为分类器设计并实现了一种多级策略的汉字识别系统。
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