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This paper addresses the problem of word spotting in handwritten documents. We propose a coarse-to-fine segmentation free approach. This approach is based on two filtering phases, which are a global filtering followed by a local filtering after changing the observation scale. The contribution of this work is the use and the adaptation of the Haarlike-features in word spotting task for each tested document and the introduction of a new technique permits modelling queries typed by the user. The approach is evaluated using the George Washington manuscripts database. MOTS-CLÉS : Word spotting, caractéristiques pseudo-Haar, analyse de documents

Adaptation des caractéristiques pseudo-Haar pour le word spotting dans les documents manuscrits