Prototype learning methods for online handwriting recognition

Raghavendra, BS and Narayanan, CK and Sita, G and Ramakrishnan, AG and Sriganesh, M (2005) Prototype learning methods for online handwriting recognition. In: Proceedings of the 2005 Eight International Conference on Document Analysis and Recognition (ICDAR’05), 29 Aug.-1 Sept. 2005.

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Abstract

In this paper, we study different methods for prototype selection for recognizing handwritten characters of Tamil script. In the first method, cumulative pairwise- distances of the training samples of a given class are used to select prototypes. In the second method, cumulative distance to allographs of different orientation is used as a criterion to decide if the sample is representative of the group. The latter method is presumed to offset the possible orientation effect. This method still uses fixed number of prototypes for each of the classes. Finally, a prototype set growing algorithm is proposed, with a view to better model the differences in complexity of different character classes. The proposed algorithms are tested and compared for both writer independent and writer adaptation scenarios.

Item Type:	Conference Paper
Publisher:	IEEE
Additional Information:	Copyright 2005 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:	08 Mar 2012 09:58
Last Modified:	08 Mar 2012 09:58
URI:	http://eprints.iisc.ac.in/id/eprint/43734

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