A method of Jia Gu Wen recognition based on a two-level classification

Author

Zhou, Xin-Lun ; Hua, Xing-Cheng ; Li, Feng

Author_Institution

Dept. of Electron. Eng., Fudan Univ., Shanghai, China

Volume

2

fYear

1995

fDate

14-16 Aug 1995

Firstpage

833

Abstract

Jia Gu Wen is the earliest Chinese character. Since it has many of the properties of drawings, common recognition methods cannot be efficiently applied. We provide a recognition method using a two-level classification. First, we regard the character as a non-directional graph and extract its topological properties. Thus we separate the JGW characters into different classes. Then, based on the definition of an extensive stroke, we extract the relevant properties of the strokes and make a second-level recognition. Experiments have shown that the recognition rate is above 95%

Keywords

character sets; feature extraction; graph theory; optical character recognition; pattern classification; Chinese character; JGW character classification; Jia Gu Wen character recognition; drawings; experiments; extensive stroke; nondirectional graph; recognition rate; topological property extraction; two-level classification; Bones; Character recognition; Engineering drawings; Equations; Graph theory; Heart; Joining processes; Shape; Writing;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on

Conference_Location

Montreal, Que.

Print_ISBN

0-8186-7128-9

Type

conf

DOI

10.1109/ICDAR.1995.602030

Filename

602030