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

Adam Ghorbel 1, 2, * Jean-Marc Ogier 1 Nicole Vincent 2
* Auteur correspondant
1 L3I - Laboratoire Informatique, Image et Interaction
2 LIPADE - EA 2517 - Laboratoire d'Informatique Paris Descartes
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.
Keywords : Haar-Like-Features IAM Handwriting Database
Type de document :
Communication dans un congrès
Céline Rémi; Lionel Prévost; Eric Anquetil. 17th Biennial Conference of the International Graphonomics Society, Jun 2015, Pointe-à-Pitre, Guadeloupe. 2015, Drawing, Handwriting Processing Analysis: New Advances and Challenges
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Dernière modification le : lundi 6 novembre 2017 - 16:28:02
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Adam Ghorbel, Jean-Marc Ogier, Nicole Vincent. Haar-like-features for query-by-string word spotting. Céline Rémi; Lionel Prévost; Eric Anquetil. 17th Biennial Conference of the International Graphonomics Society, Jun 2015, Pointe-à-Pitre, Guadeloupe. 2015, Drawing, Handwriting Processing Analysis: New Advances and Challenges. 〈hal-01165920〉

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