Fuzzy ring data for invariant handwritten Chinese character recognition

Author

Tseng, Din-Chang ; Chiu, Hung-Pin

Author_Institution

Inst. of Comput. Sci. & Electron. Eng., Nat. Central Univ., Chung-Li, Taiwan

Volume

3

fYear

1996

fDate

25-29 Aug 1996

Firstpage

94

Abstract

An invariant handwritten Chinese character recognition system is proposed. Characters can be in arbitrary location, scale, and orientation. Five invariant features are employed in this study. The first four features are used for preclassification to reduce matching time. The last feature, ring data, constructs ring-data vectors to characterize character samples and constructs weighted ring-data matrices to characterize characters to further reduce matching time. Fuzzy membership functions are defined based on these two characteristics to match characters

Keywords

character recognition; fuzzy set theory; matrix algebra; fuzzy membership functions; fuzzy ring data; invariant features; invariant handwritten Chinese character recognition; matching; preclassification; ring-data vectors; weighted ring-data matrices; Character recognition; Cognition; Computer science; Data mining; Feature extraction; Flowcharts; Fuzzy set theory; Handwriting recognition; Skeleton; Tellurium;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 1996., Proceedings of the 13th International Conference on

Conference_Location

Vienna

ISSN

1051-4651

Print_ISBN

0-8186-7282-X

Type

conf

DOI

10.1109/ICPR.1996.546801

Filename

546801