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Haar-like-features for query-by-string word spotting

Abstract : This paper addresses the problem of word spotting in handwritten documents. The method is segmentation-free and follows the query-by-string paradigm. In the paper, we focus on the first step of the whole bio-inspired process that is based on two filtering steps, which are a global filtering followed by a more local filtering after a change of observation scale. The contribution of this approach is the use and the generalization of the Haar-Like-Features for the analysis of the document images, inspired from the famous visual perception principle. Different pieces of information are extracted from the whole image before drawing a conclusion, after a process of accumulation of votes. The method is evaluated using the IAM Handwriting Database.
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Submitted on : Saturday, June 20, 2015 - 7:59:46 PM
Last modification on : Thursday, October 8, 2020 - 11:50:06 AM
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  • HAL Id : hal-01165920, version 1


Adam Ghorbel, Jean-Marc Ogier, Nicole Vincent. Haar-like-features for query-by-string word spotting. 17th Biennial Conference of the International Graphonomics Society, International Graphonomics Society (IGS); Université des Antilles (UA), Jun 2015, Pointe-à-Pitre, Guadeloupe. ⟨hal-01165920⟩



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