A robust model for on-line handwritten Japanese text recognition

Bilan Zhu; Xiang-Dong Zhou; Cheng-Lin Liu; Masaki Nakagawa

doi:10.1117/12.807060

19 January 2009 A robust model for on-line handwritten Japanese text recognition

Bilan Zhu, Xiang-Dong Zhou, Cheng-Lin Liu, Masaki Nakagawa

Proceedings Volume 7247, Document Recognition and Retrieval XVI; 72470B (2009) https://doi.org/10.1117/12.807060
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States

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.

Citation Download Citation

Bilan Zhu, Xiang-Dong Zhou, Cheng-Lin Liu, and Masaki Nakagawa "A robust model for on-line handwritten Japanese text recognition", Proc. SPIE 7247, Document Recognition and Retrieval XVI, 72470B (19 January 2009); https://doi.org/10.1117/12.807060

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available