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Journal Articles Traitement du Signal Year : 2011

Adaptive relevant feature selection and hierarchical image classification in heterogeneous databases

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Abstract

In heterogeneous databases, images often provided from different sources and belong to different topics, hence there is a need for a large description to ensure efficient representation of their content. However, extracted features are not always adapted to the considered image database. In this paper we propose a new image recognition approach based on two innovations, namely adaptive feature selection and Multi-Model Classification Method (MC-MM). The adaptive selection considers only the most adapted features with the used image database content. The MC-MM method ensures image recognition using hierarchically selected features. Experimental results confirm the effectiveness and the robustness of our proposed approach.

Dates and versions

hal-00745315 , version 1 (25-10-2012)

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Rostom Kachouri, Khalifa Djemal, Hichem Maaref. Adaptive relevant feature selection and hierarchical image classification in heterogeneous databases. Traitement du Signal, 2011, 28 (5), pp.547--574. ⟨10.3166/TS.28.547-574⟩. ⟨hal-00745315⟩
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