DocumentCode :
3318264
Title :
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
Link To Document :
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