Combining Features for image retrieval by concept lattice querying and navigation

Content-based image retrieval (CBIR for short) methods aim at capturing image similarity by relying on some specific characteristic of images such as color, texture and shape. The model we propose addresses the problem of exploring the image space applying multiple similarity criteria by representing the search for the images similar to a given image as the exploration of a lattice of (non-disjoint) image clusters, induced by a natural ordering criterion, based on similarity measures. The exploration proceeds in one of two basic ways: (1) by querying, the user can jump to any cluster of the lattice, by specifying the criteria that the sought cluster must satisfy; or (2) by navigation: from any cluster, the user can move to a neighbor cluster, thus exploiting the ordering amongst clusters.