Handwritten Character Recognition Using HMM Model Based on Bagging Method

Author

Zhang, Yan ; Yao, Xiaodong ; Chang, Ching

Author_Institution

Dept. of Electron. Inf., East China Univ. of Sci. & Technol., Shanghai, China

fYear

2009

fDate

11-13 Dec. 2009

Firstpage

1

Lastpage

4

Abstract

The purpose of this paper is to improve recognition rate of off-line handwritten character recognition system.We apply the statistical characteristics of the percentage of pixels and structural characteristics of boundary chain code of character projection, after train based on HMM to obtain corresponding parameters, then integrate different classifiers through the Bagging algorithm in Voting method. Experimental results indicate that this approach can further improve the performance.

Keywords

handwriting recognition; handwritten character recognition; hidden Markov models; Bagging algorithm; Bagging method; Voting method; boundary chain code; character projection; handwritten character recognition rate; hidden Markov models; offline handwritten character recognition system; Bagging; Character recognition; Data mining; Data preprocessing; Feature extraction; Handwriting recognition; Hidden Markov models; Image recognition; Image segmentation; Pattern recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4507-3

Electronic_ISBN

978-1-4244-4507-3

Type

conf

DOI

10.1109/CISE.2009.5366197

Filename

5366197