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19 January 2009 A robust model for on-line handwritten Japanese text recognition
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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.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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
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