Incorporating concept ontology into multi-level image indexing
Proceedings of the First International Conference on Internet Multimedia Computing and Service
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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 multi- ple 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 nat- ural 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 lat- tice, 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.