DocumentCode
1982773
Title
Study of off-line handwritten Chinese character recognition based on dynamic pruned FSVMs
Author
Zhu, Cheng-hui ; Shi, Chang-yu ; Wang, Jian-ping ; Xu, Xiao-bing
Author_Institution
Sch. of Electr. Eng. & Autom., Hefei Univ. of Technol., Hefei, China
fYear
2011
fDate
16-18 Sept. 2011
Firstpage
395
Lastpage
398
Abstract
According to the off-line handwritten Chinese characters, a classification and recognition method which is combined by pruning FSVM coarse classification and SVM fine classification is proposed in this text .First cut no value minor to reduce the number of support vector machines, and then determine the coarse classification through fuzzy membership when the coarse classification is done. In fine classification, OAA SVM algorithm is used to achieve the same Chinese characters recognition. The simulation result shows that this method can improve the recognition rate and speed of off-line handwritten Chinese.
Keywords
fuzzy set theory; handwriting recognition; image classification; natural language processing; support vector machines; FSVM coarse classification; dynamic pruned FSVM; fuzzy membership; handwritten Chinese character recognition; support vector machines; Character recognition; Classification algorithms; Complexity theory; Feature extraction; Heuristic algorithms; Support vector machines; Training; FSVM; membership; multi-classification; offline handwritten Chinese characters;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Control Engineering (ICECE), 2011 International Conference on
Conference_Location
Yichang
Print_ISBN
978-1-4244-8162-0
Type
conf
DOI
10.1109/ICECENG.2011.6057497
Filename
6057497
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