Offline handwritten chinese character recognition using optimal sampling features

被引：0
|
作者：
Zhang, R [1 ]
Ding, XQ [1 ]
机构：
[1] Tsing Hua Univ, Dept Elect Engn, State Key Lab Intelligent Technol & Syst, Beijing 100084, Peoples R China
来源：
ADVANCES IN MULTIMODAL INTERFACES - ICMI 2000, PROCEEDINGS | 2000年 / 1948卷
关键词：
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
For offline handwritten Chinese character recognition, stroke variation is the most difficult problem to be solved. A new method of optimal sampling features is proposed to compensate for the; stroke variations and decrease the within-class pattern variability, In this method, we propose the concept of sampling features based on directional features that are widely used in offline Chinese character recognition. Optimal sampling features are then developed from sampling features by displacing the sampling positions under an optimal criterion. The algorithm for extracting optimal sampling features is proposed. The effectiveness of this method is widely tested using the Tsinghua University database (THCHR).
引用
收藏
页码：458 / 465
页数：8
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