Hue class equalization to improve a hierarchical image retrieval system

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.