Unrestricted Kannada online handwritten akshara recognition using SDTW

Kunwar, Rituraj and Mohan, P and Shashikiran, K and Ramakrishnan, AG (2010) Unrestricted Kannada online handwritten akshara recognition using SDTW. In: 2010 International Conference on Signal Processing and Communications (SPCOM), 18-21 July 2010, Bangalore.

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Abstract

In this paper, we present an unrestricted Kannada online handwritten character recognizer which is viable for real time applications. It handles Kannada and Indo-Arabic numerals, punctuation marks and special symbols like $, &, # etc, apart from all the aksharas of the Kannada script. The dataset used has handwriting of 69 people from four different locations, making the recognition writer independent. It was found that for the DTW classifier, using smoothed first derivatives as features, enhanced the performance to 89% as compared to preprocessed co-ordinates which gave 85%, but was too inefficient in terms of time. To overcome this, we used Statistical Dynamic Time Warping (SDTW) and achieved 46 times faster classification with comparable accuracy i.e. 88%, making it fast enough for practical applications. The accuracies reported are raw symbol recognition results from the classifier. Thus, there is good scope of improvement in actual applications. Where domain constraints such as fixed vocabulary, language models and post processing can be employed. A working demo is also available on tablet PC for recognition of Kannada words.

Item Type:	Conference Paper
Publisher:	IEEE
Additional Information:	Copyright 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	29 Dec 2011 07:03
Last Modified:	29 Dec 2011 07:03
URI:	http://eprints.iisc.ac.in/id/eprint/42935

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