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ICPR
2000
IEEE

Precise Hand-printed Character Recognition Using Elastic Models via Nonlinear Transformation

9 years 7 months ago
Precise Hand-printed Character Recognition Using Elastic Models via Nonlinear Transformation
Distorted character recognition is a difficult but inevitable problem in hand-printed character recognition. In this paper, we propose a character recognition method using elastic models for recognizing cursive characters with intricate structure. The models are fitted to unknown input patterns by applying the EM algorithm to minimize a measure of fittness. To avoid falling into local minima, multiresolutional approach is introduced. Moreover, nonlinear transformation is adopted to realize more flexible matching. Experiments performed on Japanese characters show effectiveness of the proposed method.
Tsuyoshi Kato, Shinichiro Omachi, Hirotomo Aso
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2000
Where ICPR
Authors Tsuyoshi Kato, Shinichiro Omachi, Hirotomo Aso
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