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Kokubunji, Tokyo, Japan
Oct. 26, 2004 to Oct. 29, 2004
ISBN: 0-7695-2187-8
pp: 407-412
Henri Binsztok , Universit? Paris VI
Thierry Arti?res , Universit? Paris VI
ABSTRACT
We present an Hidden Markov Model-based approach to model on-line handwriting sequences. This problem is addressed in term of learning both Hidden Markov Models(HMM) structure and parameters from data. We iteratively simplify an initial HMM that consists in a mixture of as many left-right HMM as training sequences. There are two main applications of our approach: allograph identification and classification. We provide experimental results on these two different tasks.
INDEX TERMS
HMM Structure Learning, Allograph Clustering
CITATION
Henri Binsztok, Thierry Arti?res, "Learning HMM Structure for On-Line Handwriting Modelization", IWFHR, 2004, Proceedings. Ninth International Workshop on Frontiers in Handwriting Recognition, Proceedings. Ninth International Workshop on Frontiers in Handwriting Recognition 2004, pp. 407-412, doi:10.1109/IWFHR.2004.60
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