DocumentCode :
2396953
Title :
Handwritten Chinese character analysis and preclassification using stroke structural sequence
Author :
Chen, Zen ; Lee, Chi-Wei ; Cheng, Rei-Heng
Author_Institution :
Inst. of Comput. Sci. & Inf. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
Volume :
3
fYear :
1996
fDate :
25-29 Aug 1996
Firstpage :
89
Abstract :
A unique stroke ordering for handwritten Chinese characters is desirable in many applications including efficient character recognition and automatic radical extraction. Although there are some rules or conventions for writing Chinese characters, yet no consistent and complete rule set is available. Besides special radical knowledge is often needed. It is the purpose of this paper to propose a set of rules for stroke ordering for producing a unique stroke sequence for Chinese characters. It requires no special radical knowledge or knowledge of character block layouts, so it is easy for machine implementation. Moreover, the stroke sequences derived are similar to those given in the dictionary, if not the same. To deal with the writing, variations among writers, we generalize the derived stroke structure sequence to obtain a more consistent stroke information. This generalized stroke structural sequence can be used in the handwritten Chinese character preclassification. Experiments showing applications of our method are reported
Keywords :
character recognition; image classification; Chinese character preclassification; automatic radical extraction; character recognition; classification; handwritten Chinese character analysis; stroke ordering; stroke structural sequence; Application software; Character recognition; Computer science; Data mining; Databases; Dictionaries; Handwriting recognition; Humans; Shape; Writing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
ISSN :
1051-4651
Print_ISBN :
0-8186-7282-X
Type :
conf
DOI :
10.1109/ICPR.1996.546800
Filename :
546800
Link To Document :
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