NDLI: A system for identifying writer from Thai handwriting image

Content Provider	IEEE Xplore Digital Library
Author	U-Seng, J. Tanprasert, T.
Copyright Year	2002
Description	Author affiliation: Dept. of Comput. Sci., Assumption Univ. of Thailand, Bangkok, Thailand (U-Seng, J.; Tanprasert, T.)
Abstract	Many techniques have been reported on handwriting-based writer identification. Most of such techniques assume that the written text is fixed (e.g. in signature verification). A neural network based technique in which the written text is not fixed to identify a writer from Thai handwritten image, is presented. Without fixed text, it is much more difficult for a fake writer to sneak through the system test. Each writer has to write training set of 63 Thai characters and 25 testing sentences. The results of 99.43% accuracy on the classification of 250 test documents from 10 writers are very promising.
Sponsorship	Asia-Pacific Neural Network Assembly Singapore Neuroscience Assoc. SEAL & FSKD Conference Steering Committees IEEE Neural Networks Soc. Int. Neural Network Soc. Eur. Neural Network Soc. SPIE
Starting Page	631
Ending Page	635
File Size	419362
Page Count	5
File Format	PDF
ISBN	9810475241
DOI	10.1109/ICONIP.2002.1198134
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-11-18
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Nanyang Technological University
Subject Keyword	Handwriting recognition Testing Character recognition Writing Biometrics Computer science Neural networks Transducers Protection Personal communication networks
Content Type	Text
Resource Type	Article

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