Nonlinear active handwriting models and their applications to handwritten chinese radical recognition

被引：0

作者：

Ng, GS ^{[1
]}

Shi, D ^{[1
]}

Gunn, SR ^{[1
]}

Damper, RI ^{[1
]}

机构：

[1] Nanyang Technol Univ, Sch Comp Engn, Singapore 639798, Singapore

来源：

SEVENTH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION, VOLS I AND II, PROCEEDINGS | 2003年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes active handwriting models, in which kernel principal component analysis is applied to capture nonlinear handwriting variations. In the recognition phase, the chamfer distance transform and a dynamic tunnelling algorithm (DTA) are employed to search for the optimal shape parameters. The proposed methodology is successfully applied to a novel radical decomposition approach to the challenging problem of handwritten Chinese character recognition.

引用

页码：534 / 538

页数：5

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