Rejection strategies for offline handwritten text line recognition

被引：21

作者：

Bertolami, Roman ^{[1
]}

Zimmermann, Matthias ^{[1
]}

Bunke, Horst ^{[1
]}

机构：

[1] Univ Bern, Inst Comp Sci & Appl Math, CH-3012 Bern, Switzerland

来源：

PATTERN RECOGNITION LETTERS | 2006年 / 27卷 / 16期

基金：

瑞士国家科学基金会;

关键词：

handwritten text recognition; rejection strategies; statistical language model;

D O I：

10.1016/j.patrec.2006.06.002

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper investigates rejection strategies for unconstrained offline handwritten text line recognition. The rejection strategies depend on various confidence measures that are based on alternative word sequences. The alternative word sequences are derived from specific integration of a statistical language model in the hidden Markov model based recognition system. Extensive experiments on the IAM database validate the proposed schemes and show that the novel confidence measures clearly outperform two baseline systems which use normalised likelihoods and local n-best lists, respectively. (c) 2006 Elsevier B.V. All rights reserved.

引用

页码：2005 / 2012

页数：8

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