Using indexing structures for resource descriptors extraction from distributed image repositories
Content based retrieval from distributed libraries raises new and challenging issues with respect to retrieval from a single repository. In particular, an effective management of distributed libraries develops upon three main processes: resource description (extraction of descriptors that qualify the content of a given archive), resource selection (given a user query, analyze resource descriptions and select the resources that contain relevant documents) and results merging (organize and present items returned by individual libraries). So far, these issues have been mainly addressed for text archives. We present a solution to resource descriptors extraction, developing on the use of techniques for multidimensional data indexing. In particular, we implement and compare the extraction of resource descriptors computed through two different indexing approaches; namely m-tree indexing and fuzzy clustering. Comparative results are presented for a test database of about 1000 images.