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Ninth International Workshop on Frontiers in Handwriting Recognition (2004)
Kokubunji, Tokyo, Japan
Oct. 26, 2004 to Oct. 29, 2004
ISSN: 1550-5235
ISBN: 0-7695-2187-8
pp: 407-412
Thierry Arti?res , Universit? Paris VI
Henri Binsztok , Universit? Paris VI
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.
HMM Structure Learning, Allograph Clustering
Thierry Arti?res, Henri Binsztok, "Learning HMM Structure for On-Line Handwriting Modelization", Ninth International Workshop on Frontiers in Handwriting Recognition, vol. 00, no. , pp. 407-412, 2004, doi:10.1109/IWFHR.2004.60
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