NDLI: Study of Different Features on Handwritten Devnagari Character

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Study of Different Features on Handwritten Devnagari Character

Content Provider	IEEE Xplore Digital Library
Author	Arora, S. Bhattacharjee, D. Nasipuri, M. Basu, D.K. Kundu, M. Malik, L.
Copyright Year	2009
Abstract	In this paper a scheme for offline Handwritten Devnagari Character Recognition is proposed, which uses different feature extraction and recognition algorithms. The proposed system assumes no constraints in writing style, size or variations. First the character is preprocessed and features namely : Chain code histogram, four side views, shadow based are extracted and fed to Multilayer Perceptrons as a preliminary recognition step. Finally the results of all MLP's are combined using weighted majority scheme. The proposed system is tested on 1500 handwritten devnagari character database collected from different people. It is observed that the proposed system achieves 98.16% recognition rates as top 5 results and 89.58% as top 1 results.
Starting Page	929
Ending Page	933
File Size	436947
Page Count	5
File Format	PDF
ISBN	9781424452507
DOI	10.1109/ICETET.2009.215
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-16
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer science Handwriting recognition Histograms Strips Natural languages Artificial neural networks Multilayer perceptrons Feature extraction Educational institutions Character recognition
Content Type	Text
Resource Type	Article

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