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
Link To Document :
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