Shape Code Based Lexicon Reduction for Offline Handwritten Word Recognition

被引：5
|
作者：
Bertolami, Roman [1 ]
Gutmann, Christoph [1 ]
Bunke, Horst [1 ]
Spitz, A. Lawrence [2 ]
机构：
[1] Univ Bern, Inst Comp Sci & Appl Math, Neubrackstr 10, CH-3012 Bern, Switzerland
[2] DocRec Ltd, Nelson 7010, New Zealand
来源：
PROCEEDINGS OF THE 8TH IAPR INTERNATIONAL WORKSHOP ON DOCUMENT ANALYSIS SYSTEMS | 2008年
基金：
瑞士国家科学基金会;
关键词：
D O I：
10.1109/DAS.2008.18
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel method to reduce the lexicon size in handwritten word recognition is proposed in this paper Due to large lexica, the computational cost of current word recognisers is often too high for practical applications. The proposed lexicon reduction method is based on character shape codes. We examine four different shape code mappings based on machine printed character font, on handprint, and on cursive handwriting. Experimental evaluation shows that the proposed method can reduce the computational effort while keeping the recognition rate high.
引用
收藏
页码：158 / +
页数：3
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