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Communication Dans Un Congrès Année : 2015

Hue class equalization to improve a hierarchical image retrieval system

William Puech
Christophe Fiorio

Résumé

This paper proposes a filtering system within a large database in order to accelerate image retrieval. A first filter is applied to the database in order to have a small number of candidates. This filter consists of a global descriptor based on color classification. Instead of the use of static classification based on the HVS (Human Visual System), the classification is based on a uniform repartition of pixels from the database. Those classes are gathered from a learning database. With this classification a global descriptor is computed based on hue, saturation and lightness. An equiprobability of each pixel is assigned to each class, this allows us to have a more constant reduction for the requested image and to have better filtering of the candidates. A more powerful and time consuming method can be used then for identifying the best candidate.
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Dates et versions

lirmm-01273971 , version 1 (15-03-2016)

Identifiants

Citer

Tristan d'Anzi, William Puech, Christophe Fiorio, Jérémie François. Hue class equalization to improve a hierarchical image retrieval system. IPTA: Image Processing Theory, Tools and Applications, Nov 2015, Orléans, France. pp.561-566, ⟨10.1109/IPTA.2015.7367210⟩. ⟨lirmm-01273971⟩
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