Nonlinear Active Handwriting Models and Their Applications to Handwritten Chinese Radical Recognition

Authors:
G. S. Ng;D. Shi;S. R. Gunn;R. I. Damper
Affiliations:
-;-;-;-
Venue:
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Year:
2003

Citing 7
Cited 0

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Abstract

This paper proposes active handwriting models, inwhich kernel principal component analysis is applied tocapture nonlinear handwriting variations. In the recognitionphase, the chamfer distance transform and a dynamictunnelling algorithm (DTA) are employed to search for theoptimal shape parameters. The proposed methodology issuccessfully applied to a novel radical decomposition approachto the challenging problem of handwritten Chinesecharacter recognition.