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Proceedings Paper

Retrieving handwriting by combining word spotting and manifold ranking
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Paper Abstract

Online handwritten data, produced with Tablet PCs or digital pens, consists in a sequence of points (x, y). As the amount of data available in this form increases, algorithms for retrieval of online data are needed. Word spotting is a common approach used for the retrieval of handwriting. However, from an information retrieval (IR) perspective, word spotting is a primitive keyword based matching and retrieval strategy. We propose a framework for handwriting retrieval where an arbitrary word spotting method is used, and then a manifold ranking algorithm is applied on the initial retrieval scores. Experimental results on a database of more than 2,000 handwritten newswires show that our method can improve the performances of a state-of-the-art word spotting system by more than 10%.

Paper Details

Date Published: 23 January 2012
PDF: 8 pages
Proc. SPIE 8297, Document Recognition and Retrieval XIX, 82970X (23 January 2012); doi: 10.1117/12.910638
Show Author Affiliations
Sebastián Peña Saldarriaga, Synchromedia (Canada)
Emmanuel Morin, Lab. Informatique de Nantes Atlantique, CNRS, Univ. de Nantes (France)
Christian Viard-Gaudin, Institut de Recherche en Communications et Cybernétique de Nantes, CNRS, Univ. de Nantes (France)

Published in SPIE Proceedings Vol. 8297:
Document Recognition and Retrieval XIX
Christian Viard-Gaudin; Richard Zanibbi, Editor(s)

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