16th International Conference on Pattern Recognition (ICPR'02) - Volume 3
DVHMM: Variable Length Text Recognition Error Model
Quebec City, QC, Canada
August 11-August 15
ISBN: 0-7695-1695-X
This paper proposes a text recognition error model called the dual variable length output hidden Markov model (DVHMM) and gives a parameter estimation algorithm based on the EM algorithm. Although existing probabilistic error models are limited to substitution (1,1), insertion (1,0), and deletion (0,1) errors, the DVHMM can handle error patterns of any pair (i, j) of lengths including substitution, insertion, and deletion.
Citation:
Atsuhiro Takasu, Kenro Aihara, "DVHMM: Variable Length Text Recognition Error Model," icpr, vol. 3, pp.30110, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 3, 2002