NDLI: Handwritten Chinese character recognition using kernel active handwriting model

Content Provider	IEEE Xplore Digital Library
Author	Daming Shi Yew Soon Ong Eng Chong Tan
Copyright Year	2003
Description	Author affiliation: Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore (Daming Shi; Yew Soon Ong; Eng Chong Tan)
Abstract	This paper describes a kernel active handwriting model (K-AHM) and its application to handwritten Chinese character recognition. In the model, the kernel principal component analysis is applied to capture nonlinear variations caused by handwriting, and a fitness function on the basis of a chamfer distance transform is introduced to search for optimal shape parameters using genetic algorithms (GAs). The K-AHM is applied to handwritten Chinese character recognition, which converts the complex pattern recognition problem into recognizing a small set of primitive structures called radicals. By treating Chinese character composition as a discrete-time Markov process, character composition is carried out with the Viterbi algorithm. The proposed methodology has been successfully implemented in an experimental recognition system.
Sponsorship	Syst., Man & Cybernetics Soc. IEEE
Starting Page	251
Ending Page	255
File Size	319421
Page Count	5
File Format	PDF
ISBN	0780379527
ISSN	1062922X
DOI	10.1109/ICSMC.2003.1243824
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-10-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Character recognition Kernel Pattern recognition Principal component analysis Discrete transforms Shape Genetic algorithms Handwriting recognition Markov processes Viterbi algorithm
Content Type	Text
Resource Type	Article

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