NDLI: Normalization ensemble for handwritten character recognition

Content Provider	IEEE Xplore Digital Library
Author	Cheng-Lin Liu Marukawa, K.
Copyright Year	2004
Description	Author affiliation: Central Res. Lab., Hitachi Ltd., Tokyo, Japan (Cheng-Lin Liu; Marukawa, K.)
Abstract	This paper proposes a multiple classifier approach, called normalization ensemble, for handwritten character recognition by combining multiple normalization methods. By varying the coordinate mapping mode, we have devised 14 normalization functions, and switching on/off slant correction results in 28 instantiated classifiers. We would show that the classifiers with different normalization methods are complementary and the combination of them can significantly improve the recognition accuracy. In experiments of handwritten digit recognition on the NIST special database 19, the normalization ensemble was shown to reduce the error rate by factors from 10.6% to 26.9% and achieved the best error rate 0.43%. We also show that the complexity of normalization ensemble can be reduced by selecting seven classifiers from 28 with little loss of accuracy.
Sponsorship	Hitachi, Japan IBM, USA Fujitsu Lab., Japan NEC, Japan Toshiba, Japan Microsoft, USA Int. Assoc. for Pattern Recognition
Starting Page	69
Ending Page	74
File Size	235508
Page Count	6
File Format	PDF
ISBN	0769521878
ISSN	15505235
DOI	10.1109/IWFHR.2004.76
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-10-26
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Character recognition Handwriting recognition Diversity reception Feature extraction NIST Error analysis Laboratories Databases Training data Filtering
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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