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Proceedings Paper

Visual similarity analysis of Chinese characters and its uses in Japanese OCR
Author(s): Tao Hong; Stephen W. Lam; Jonathan J. Hull; Sargur N. Srihari
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Paper Abstract

Traditionally, a Chinese or Japanese optical character reader (OCR) has to represent each character category individually as one or more feature prototypes, or a structural description which is a composition of manually derived components such as radicals. Here we propose a new approach in which various kinds of visual similarities between different Chinese characters are analyzed automatically at the feature level. Using this method, character categories are related to each other by training on fonts; and character images from a text page can be related to each other based on the visual similarities they share. This method provides a way to interpret character images from a text page systematically, instead of a sequence of isolated character recognitions. The use of the method for post processing in Japanese text recognition is also discussed.

Paper Details

Date Published: 30 March 1995
PDF: 9 pages
Proc. SPIE 2422, Document Recognition II, (30 March 1995); doi: 10.1117/12.205827
Show Author Affiliations
Tao Hong, SUNY/Buffalo (United States)
Stephen W. Lam, SUNY/Buffalo (United States)
Jonathan J. Hull, Ricoh California Research Ctr. (United States)
Sargur N. Srihari, SUNY/Buffalo (United States)

Published in SPIE Proceedings Vol. 2422:
Document Recognition II
Luc M. Vincent; Henry S. Baird, Editor(s)

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