Nonlinear active handwriting models and their applications to handwritten Chinese radical recognition

Author

Ng, G.S. ; Shi, D. ; Gunn, S.R. ; Damper, R.I.

Author_Institution

Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore

fYear

2003

fDate

3-6 Aug. 2003

Firstpage

534

Abstract

This paper proposes active handwriting models, in which kernel principal component analysis is applied to capture nonlinear handwriting variations. In the recognition phase, the chamfer distance transform and a dynamic tunneling algorithm (DTA) are employed to search for the optimal shape parameters. The proposed methodology is successfully applied to a novel radical decomposition approach to the challenging problem of handwritten Chinese character recognition.

Keywords

character sets; handwriting recognition; handwritten character recognition; optical character recognition; principal component analysis; DTA; chamfer distance transform; dynamic tunneling algorithm; handwriting variation; handwritten Chinese radical recognition; nonlinear active handwriting model; optimal shape parameter; principal component analysis; radical decomposition approach; recognition phase; Active shape model; Application software; Character recognition; Deformable models; Handwriting recognition; Image recognition; Kernel; Performance analysis; Principal component analysis; Speech recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition, 2003. Proceedings. Seventh International Conference on

Print_ISBN

0-7695-1960-1

Type

conf

DOI

10.1109/ICDAR.2003.1227722

Filename

1227722