Handwriting digit recognition based on extension engineering

Author

Xiao, Huimin ; Liu, Chen

Author_Institution

Inf. Sch., Henan Univ. of Finance & Econ., Zhengzhou, China

fYear

2009

fDate

17-19 June 2009

Firstpage

2915

Lastpage

2918

Abstract

The complicated training algorithm is needed in the traditional handwriting digits recognition, the complexity of algorithm is very high, and the expansibility to huge database is small. In this paper, the handwriting digit is recognized by means of the extension engineering. The classical domains and the extensional domains of handwriting digit character are constructed. The integrated correlative degrees of the measuring digits and 10 basic digits are calculated and handwriting digits are classified and recognized. According to the calculated correlative degrees and the recognized results, extension engineering is an effective method to handwriting digit recognition.

Keywords

handwriting recognition; handwritten character recognition; support vector machines; complicated training algorithm; extension engineering; handwriting digit character recognition; support vector machine; Data engineering; Databases; Defense industry; Finance; Forward contracts; Handwriting recognition; Image recognition; Pattern recognition; Support vector machine classification; Support vector machines; Classification; Extension engineering; Handwriting digit recognition; Support vector machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference, 2009. CCDC '09. Chinese

Conference_Location

Guilin

Print_ISBN

978-1-4244-2722-2

Electronic_ISBN

978-1-4244-2723-9

Type

conf

DOI

10.1109/CCDC.2009.5192803

Filename

5192803