JIPS (Çѱ¹Á¤º¸Ã³¸®ÇÐȸ)
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ÇѱÛÁ¦¸ñ(Korean Title) |
Online Recognition of Handwritten Korean and English Characters |
¿µ¹®Á¦¸ñ(English Title) |
Online Recognition of Handwritten Korean and English Characters |
ÀúÀÚ(Author) |
Ming Ma
Dong-Won Park
Soo Kyun Kim
Syungog An
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¿ø¹®¼ö·Ïó(Citation) |
VOL 08 NO. 04 PP. 0653 ~ 0668 (2012. 12) |
Çѱ۳»¿ë (Korean Abstract) |
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¿µ¹®³»¿ë (English Abstract) |
In this study, an improved HMM based recognition model is proposed for online English and Korean handwritten characters. The pattern elements of the handwriting model are sub character strokes and ligatures. To deal with the problem of handwriting style variations, a modified Hierarchical Clustering approach is introduced to partition different writing styles into several classes. For each of the English letters and each primitive grapheme in Korean characters, one HMM that models the temporal and spatial variability of the handwriting is constructed based on each class. Then the HMMs of Korean graphemes are concatenated to form the Korean character models. The recognition of handwritten characters is implemented by a modified level building algorithm, which incorporates the Korean character combination rules within the efficient network search procedure. Due to the limitation of the HMM based method, a postprocessing procedure that takes the global and structural features into account is proposed. Experiments showed that the proposed recognition system achieved a high writer independent recognition rate on unconstrained samples of both English and Korean characters. The comparison with other schemes of HMM-based recognition was also performed to evaluate the system |
Å°¿öµå(Keyword) |
Online Handwriting Recognition
Hidden Markov Model
Stochastic Grammar
Hierarchical Clustering
Position Verifier
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ÆÄÀÏ÷ºÎ |
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