An off-line large vocabulary hand-written Chinese character recognizer

Author

Wong, Pak-Kwong ; Chan, Chorkin

Author_Institution

Dept. of Comput. Sci., Hong Kong Univ., Hong Kong

Volume

3

fYear

1997

Firstpage

324

Abstract

An off-line hand-written Chinese character recognizer based on contextual vector quantization (CVQ) supporting a vocabulary of 4616 Chinese characters, alphanumerics and punctuation symbols has been reported. Trained with a sample for each character from each of 100 writers and tested on texts of 160000 characters written by another 200 writers, the average recognition rate is 77.2%. Two statistical language models have been investigated in this study. Their performance in terms of their capabilities in upgrading the recognition rate by 8.8% and 12.0% respectively when used as post-processors of the recognizer are reported

Keywords

character recognition; image coding; natural languages; speech recognition; statistical analysis; vector quantisation; alphanumerics; average recognition rate; contextual vector quantization; hand-written Chinese character recognizer; off-line large vocabulary recognition; performance; post-processors; punctuation symbols; statistical language models; Character recognition; Computer science; Image recognition; Pattern recognition; Pixel; Stochastic processes; Testing; Text recognition; Vector quantization; Vocabulary;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1997. Proceedings., International Conference on

Conference_Location

Santa Barbara, CA

Print_ISBN

0-8186-8183-7

Type

conf

DOI

10.1109/ICIP.1997.632106

Filename

632106