A new approach for off-line handwritten Chinese character recognition using self-adaptive HMM

Author

Li, Jie ; Wang, Jiaxin ; Zhao, Yannan ; Yang, Zehong

Author_Institution

Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China

Volume

5

fYear

2004

Firstpage

4165

Abstract

Research on off-line handwritten Chinese character recognition is an important, yet difficult field of artificial intelligence and pattern recognition. In this paper, a kind of pseudo 2D HMM is established to solve the problem. This HMM has a special topology and is a powerful tool for modeling the Chinese handwriting. Furthermore, a self-adaptive design method is applied to this HMM and proved to be able to bring better performance to the HMM classifier. Finally, recognition experiments show that the proposed HMM has a high correct rate of 95.9%.

Keywords

handwritten character recognition; hidden Markov models; pattern classification; artificial intelligence; offline handwritten Chinese character recognition; pattern classification; pattern recognition; pseudo 2D HMM; self adaptive HMM; self adaptive design; Artificial intelligence; Buildings; Character recognition; Design methodology; Hidden Markov models; Image recognition; Intelligent systems; Laboratories; Probability density function; Topology;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on

Print_ISBN

0-7803-8273-0

Type

conf

DOI

10.1109/WCICA.2004.1342292

Filename

1342292