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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/15644
Title: A novel feature extraction approach for online Bengali and Devanagari character recognition
Authors: Ghosh R.
Pratim Roy, Partha
Published in: Proceedings of 2nd International Conference on Signal Processing and Integrated Networks, SPIN 2015
Abstract: This paper presents an online handwritten character recognition system for two major Indic scripts-Bengali and Devanagari. In this proposal, a novel approach for feature extractions is described in which each online stroke information of a character is divided into a number of local zones. For each online stroke information different structural and directional features are extracted separately in each of these local zones. Next, these features are concatenated and fed to SVM classifier for recognition. The character recognition accuracy obtained is 87.48% for Bengali script and 84.10% for Devanagari script on 4900 and 5000 test samples respectively. © 2015 IEEE.
Citation: Proceedings of 2nd International Conference on Signal Processing and Integrated Networks, SPIN 2015, (2015), 483- 488
URI: https://doi.org/10.1109/SPIN.2015.7095313
http://repository.iitr.ac.in/handle/123456789/15644
Issue Date: 2015
Publisher: Institute of Electrical and Electronics Engineers Inc.
Keywords: character recognition
Online handwriting
SVM
zone-wise features
ISBN: 9.78148E+12
Author Scopus IDs: 36025087600
56880478500
Author Affiliations: Ghosh, R., CSE Department, National Institute of Technology, Patna, India
Roy, P.P., CSE Department, National Institute of Technology, Patna, India
Appears in Collections:Conference Publications [CS]

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