HMM-based handwritten symbol recognition using on-line and off-line features

Authors:
H.-J. Winkler
Affiliations:
Inst. for Human-Machine-Commun., Tech. Univ. Munchen, Germany
Venue:
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 06
Year:
1996

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Recognition of on-line handwritten mathematical expressions using 2D stochastic context-free grammars and hidden Markov models

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Abstract

This paper addresses the problem of recognizing on-line sampled handwritten symbols. Within the proposed symbol recognition system based on hidden Markov models different kinds of feature extraction algorithms are used analysing on-line features as well as off-line features and combining the classification results. By conducting writer-dependent recognition experiments, it is demonstrated that the recognition rates as well as the reliability of the results is improved by using the proposed recognition system. Furthermore, by applying handwriting data not representing symbols out of the given alphabet, an increase of their rejection rate is obtained.