Discriminative HMM training with GA for handwritten word recognition

Author

Bhowmik, Tapan K. ; Parui, Swapan K. ; Roy, Utpal

Author_Institution

CVPR Unit, Indian Stat. Inst., Kolkata

fYear

2008

fDate

8-11 Dec. 2008

Firstpage

1

Lastpage

4

Abstract

This paper presents a recognition system for isolated handwritten Bangla words, with a fixed lexicon, using a left-right hidden Markov model (HMM). A stochastic search method, namely, genetic algorithm (GA) is used to train the HMM. A new shape based direction encoding features has been developed and introduced in our recognition system. Both non-discriminative and discriminative training procedures have been applied iteratively to optimize the parameters of HMM.

Keywords

genetic algorithms; handwriting recognition; handwritten character recognition; hidden Markov models; natural language processing; discriminative HMM training; genetic algorithm; handwritten Bangla word recognition; offline handwriting recognition system; shape based direction encoding features; stochastic search method; Encoding; Feature extraction; Genetic algorithms; Handwriting recognition; Hidden Markov models; Maximum likelihood estimation; Probability distribution; Search methods; Shape; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2008. ICPR 2008. 19th International Conference on

Conference_Location

Tampa, FL

ISSN

1051-4651

Print_ISBN

978-1-4244-2174-9

Electronic_ISBN

1051-4651

Type

conf

DOI

10.1109/ICPR.2008.4761830

Filename

4761830