DocumentCode :
2145535
Title :
Effects of Generating a Large Amount of Artificial Patterns for On-line Handwritten Japanese Character Recognition
Author :
Chen, Bin ; Zhu, Bilan ; Nakagawa, Masaki
Author_Institution :
Dept. of Comput. & Inf. Sci., Tokyo Univ. of Agric. & Technol., Tokyo, Japan
fYear :
2011
fDate :
18-21 Sept. 2011
Firstpage :
663
Lastpage :
667
Abstract :
This paper describes effects of a large amount of artificial patterns to train an on-line handwritten Japanese character recognizer. In general, as more learning patterns employed for training pattern recognition systems, as higher recognition rate is obtained. In reality, however, the existing pattern samples are not enough, especially for languages of a large character set. Therefore, for on-line handwritten Japanese character recognition, we construct six linear distortion models and combine them with a nonlinear distortion model to generate a large amount of artificial patterns. We apply the method for the TUAT Nakayosi database and train a recognizer while evaluate the effects for the TUAT Kuchibue database with the remarkable effects of improving recognition accuracy.
Keywords :
handwriting recognition; handwritten character recognition; natural languages; pattern recognition; TUAT Kuchibue database; TUAT Nakayosi database; artificial pattern; learning pattern; nonlinear distortion model; online handwritten Japanese character recognition; pattern recognition; Accuracy; Character recognition; Databases; Handwriting recognition; Nonlinear distortion; Training; Nonlinear distortion model; artificial patterns; linear distortion models; online handwriting recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location :
Beijing
ISSN :
1520-5363
Print_ISBN :
978-1-4577-1350-7
Electronic_ISBN :
1520-5363
Type :
conf
DOI :
10.1109/ICDAR.2011.139
Filename :
6065394
Link To Document :
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