Title :
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
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;
Conference_Titel :
Image Processing, 1997. Proceedings., International Conference on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
0-8186-8183-7
DOI :
10.1109/ICIP.1997.632106
