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Proceedings Paper

A robust model for on-line handwritten Japanese text recognition
Author(s): Bilan Zhu; Xiang-Dong Zhou; Cheng-Lin Liu; Masaki Nakagawa
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Paper Abstract

This paper describes a robust model for on-line handwritten Japanese text recognition. The method evaluates the likelihood of candidate segmentation paths by combining scores of character pattern size, inner gap, character recognition, single-character position, pair-character position, likelihood of candidate segmentation point and linguistic context. The path score is insensitive to the number of candidate patterns and the optimal path can be found by the Viterbi search. In experiments of handwritten Japanese sentence recognition, the proposed method yielded superior performance.

Paper Details

Date Published: 19 January 2009
PDF: 8 pages
Proc. SPIE 7247, Document Recognition and Retrieval XVI, 72470B (19 January 2009); doi: 10.1117/12.807060
Show Author Affiliations
Bilan Zhu, Tokyo Univ. of Agriculture and Technology (Japan)
Xiang-Dong Zhou, Institute of Automation (China)
Cheng-Lin Liu, Institute of Automation (China)
Masaki Nakagawa, Tokyo Univ. of Agriculture and Technology (Japan)

Published in SPIE Proceedings Vol. 7247:
Document Recognition and Retrieval XVI
Kathrin Berkner; Laurence Likforman-Sulem, Editor(s)

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