Performance enhancement of online handwritten Tamil symbol recognition with reevaluation techniques

Sundaram, Suresh and Ramakrishnan, AG (2014) Performance enhancement of online handwritten Tamil symbol recognition with reevaluation techniques. In: PATTERN ANALYSIS AND APPLICATIONS, 17 (3). pp. 587-609.

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Abstract

In this article, we aim at reducing the error rate of the online Tamil symbol recognition system by employing multiple experts to reevaluate certain decisions of the primary support vector machine classifier. Motivated by the relatively high percentage of occurrence of base consonants in the script, a reevaluation technique has been proposed to correct any ambiguities arising in the base consonants. Secondly, a dynamic time-warping method is proposed to automatically extract the discriminative regions for each set of confused characters. Class-specific features derived from these regions aid in reducing the degree of confusion. Thirdly, statistics of specific features are proposed for resolving any confusions in vowel modifiers. The reevaluation approaches are tested on two databases (a) the isolated Tamil symbols in the IWFHR test set, and (b) the symbols segmented from a set of 10,000 Tamil words. The recognition rate of the isolated test symbols of the IWFHR database improves by 1.9 %. For the word database, the incorporation of the reevaluation step improves the symbol recognition rate by 3.5 % (from 88.4 to 91.9 %). This, in turn, boosts the word recognition rate by 11.9 % (from 65.0 to 76.9 %). The reduction in the word error rate has been achieved using a generic approach, without the incorporation of language models.

Item Type:	Journal Article
Publication:	PATTERN ANALYSIS AND APPLICATIONS
Additional Information:	Copy right for this article belongs to the SPRINGER, 233 SPRING ST, NEW YORK, NY 10013 USA
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	22 Aug 2014 11:36
Last Modified:	23 Oct 2018 10:32
URI:	http://eprints.iisc.ac.in/id/eprint/49653

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