A symmetry-based coarse classification method for Chinese characters

Kuo Chin Fan, Wei Hsien Wu, Meng Pang Chung

研究成果: 雜誌貢獻期刊論文同行評審

摘要

In this paper, we present a novel symmetry-based coarse classification method for the preclassification of printed Chinese characters. The proposed method consists of two main modules, recursive radical extraction, and a symmetry test. The former classifies Chinese characters into ten classes according to the composing structure of the characters. Two classes in the ten classes, left-right, and up-down type characters, contain over 85% of the total characters. The latter performs the symmetry test to determine whether the character, or radical in the ten classes, is symmetric or not. The main purpose of the proposed symmetry-test coarse classification method is to reduce the number of characters in each of the ten classes. Four symmetry features are devised to perform the symmetry test. Experimental results reveal that the proposed method can greatly reduce the number of characters in each class to achieve the coarse classification goal.

原文???core.languages.en_GB???
頁(從 - 到)522-528
頁數7
期刊IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews
32
發行號4
DOIs
出版狀態已出版 - 11月 2002

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