Presentation 2008-02-22
Investigation of using pen-coordinate and pen-directive features by HMM in the online character recognition
Yoshinori KATAYAMA, Seiichi UCHIDA, Hiroaki SAKOE,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) A new hidden Markov model (HMM) is proposed to represent character strokes of on-line handwriting patterns. The proposed HMM deals with two typical features describing strokes, pen-direction feature and pen-coordinate feature. These two features are quite different in their stationarity; the pen-direction feature is stationary within every line segment of strokes whereas the pen-coordinate feature is not. To deal with these contrasting features by a single HMM, they are used selectively in the HMM. Specifically speaking, the pen-direction feature is output repeatedly at the intra-state transition whereas the pen-coordinate feature is output once at the inter-state transition. The usefulness of the proposed HMM over the conventional HMMs were shown through stroke order-free Chinese character recognition experiments.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) online character recognition / hidden Markov model / selective use of features
Paper # PRMU2007-229
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Conference Information
Committee PRMU
Conference Date 2008/2/14(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Investigation of using pen-coordinate and pen-directive features by HMM in the online character recognition
Sub Title (in English)
Keyword(1) online character recognition
Keyword(2) hidden Markov model
Keyword(3) selective use of features
1st Author's Name Yoshinori KATAYAMA
1st Author's Affiliation Faculty of Information Science and Electrical Engineering, Kyushu University()
2nd Author's Name Seiichi UCHIDA
2nd Author's Affiliation Faculty of Information Science and Electrical Engineering, Kyushu University
3rd Author's Name Hiroaki SAKOE
3rd Author's Affiliation Faculty of Information Science and Electrical Engineering, Kyushu University
Date 2008-02-22
Paper # PRMU2007-229
Volume (vol) vol.107
Number (no) 491
Page pp.pp.-
#Pages 6
Date of Issue