Hierarchical visual thesaurus building for satellite image retrieval based on semantic region labelling

Query by visual example (QBVE) has been widely exploited in image retrieval. If starting image is missing, the query by visual thesaurus paradigm allows the user to compose his mental query image through visual patches summarizing the region database. Researches on the human visual system have provided considerable evidence that the color and texture must be processed separately. In this paper, we propose to enrich the paradigm of mental image search by constructing a hierarchical visual thesaurus of the regions provided by a new region labeling criterion into homogeneous and textured regions for boosting the object recognition. The new labeling criterion is based on the spatial dispersion of interest points in the region. Our point based criterion has been validated on a satellite image database. We can prove that our approach is able to retrieve complex concepts better than describing homogeneous and textured regions with the same visual feature.