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Communication Dans Un Congrès Année : 2009

A Symbol Spotting Approach Based on the Vector Model and a Visual Vocabulary

Résumé

This paper addresses the difficult problem of symbol spotting for graphic documents. We propose an approach where each graphic document is indexed as a text document by using the vector model and an inverted file structure. The method relies on a visual vocabulary built from a shape descriptor adapted to the document level and invariant under classical geometric transforms (rotation, scaling and translation). Regions of interest selected with high degree of confidence using a voting strategy are considered as occurrences of a query symbol. Experimental results are promising and show the feasibility of our approach.
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Dates et versions

inria-00431186 , version 1 (10-11-2009)

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Thi Oanh Nguyen, Salvatore Tabbone, Alain Boucher. A Symbol Spotting Approach Based on the Vector Model and a Visual Vocabulary. 10th International Conference on Document Analysis and Recognition - ICDAR 2009, Jul 2009, Barcelona, Spain. pp.708-712, ⟨10.1109/ICDAR.2009.207⟩. ⟨inria-00431186⟩
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