Combining multiple classifiers based on statistical method for handwritten Chinese character recognition

Author

Lin, Lei ; Wang, Xiao-long ; Liu, Bing-quan

Author_Institution

Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., China

Volume

1

fYear

2002

fDate

2002

Firstpage

252

Abstract

In various application areas of pattern recognition, combining multiple classifiers is regarded as a method for achieving a substantial gain in performance of systems. The paper presents a method for handwritten Chinese character recognition to combine multiple classifiers based on statistics. Fusion strategies are discussed for providing a basis for combining classifiers. These combination strategies are experimentally tested on an online handwritten Chinese character recognition system. In our experiments, other combination approaches are also involved for comparison.

Keywords

Bayes methods; decision theory; handwritten character recognition; probability; classifiers; fusion strategies; handwritten Chinese character recognition; online recognition system; pattern recognition; statistical method; Application software; Bayesian methods; Character recognition; Computer science; Electronic mail; Handwriting recognition; Pattern recognition; Performance gain; Statistical analysis; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on

Print_ISBN

0-7803-7508-4

Type

conf

DOI

10.1109/ICMLC.2002.1176750

Filename

1176750