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Proceedings Paper

Pyramid multiresolution classifier for online large vocabulary Chinese character recognition
Author(s): Quen-Zong Wu; I-Chang Jou; Yann Le Cunn
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Paper Abstract

A pyramid classifier is proposed for large vocabulary Chinese characters, which at first uses low resolution features to roughly classify the input character, and then used higher resolution features to make finer classification stage by stage. In addition to the rule- based preclassification, there are three stages to achieve recognition. The number of candidate categories is reduced step by step. We use one thousand categories of Chinese characters for experiments. Simulation results show that this classifier can recognize the input character with 93.1% and 90% accuracy on the training set and the test set respectively.

Paper Details

Date Published: 21 April 1995
PDF: 8 pages
Proc. SPIE 2501, Visual Communications and Image Processing '95, (21 April 1995); doi: 10.1117/12.206703
Show Author Affiliations
Quen-Zong Wu, Telecommunication Labs. (Taiwan)
I-Chang Jou, Telecommunication Labs. (Taiwan)
Yann Le Cunn, AT&T Bell Labs. (United States)


Published in SPIE Proceedings Vol. 2501:
Visual Communications and Image Processing '95
Lance T. Wu, Editor(s)

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