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Hidden Markov models applied to on-line handwritten isolated character recognition

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2 Author(s)
Veltman, S.R. ; Telecommun. & Traffic-Control Syst. Group, Delft Univ. of Technol., Netherlands ; Prasad, R.

Hidden Markov models are used to model the generation of handwritten, isolated characters. Models are trained on examples using the Baum-Welch optimization routine. Then, given the models for the alphabet, unknown characters can be classified using maximum-likelihood classification. Experiments have been conducted, and an average error rate of 6.9% was achieved over the alphabet consisting of the lowercase English alphabet

Published in:

Image Processing, IEEE Transactions on  (Volume:3 ,  Issue: 3 )