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Localization of handwritten text in documents using moment invariants and Delaunay triangulation

Ramakrishnan, Kandan and Arvind, KR and Ramakrishnan, AG (2007) Localization of handwritten text in documents using moment invariants and Delaunay triangulation. In: 7th International Conference on Computational Intelligence and Multimedia Applications, DEC 13-15, 2007, Sivakasi, Tamil Nadu.

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Abstract

This paper describes an approach based on Zernike moments and Delaunay triangulation for localization of hand-written text in machine printed text documents. The Zernike moments of the image are first evaluated and we classify the text as hand-written using the nearest neighbor classifier. These features are independent of size, slant, orientation, translation and other variations in handwritten text. We then use Delaunay triangulation to reclassify the misclassified text regions. When imposing Delaunay triangulation on the centroid points of the connected components, we extract features based on the triangles and reclassify the text. We remove the noise components in the document as part of the preprocessing step so this method works well on noisy documents. The success rate of the method is found to be 86%. Also for specific hand-written elements such as signatures or similar text the accuracy is found to be even higher at 93%.

Item Type: Conference Paper
Additional Information: Copyright 2007 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 Mar 2010 11:13
Last Modified: 19 Sep 2010 05:57
URI: http://eprints.iisc.ernet.in/id/eprint/26305

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