A classification-matching combination for image retrieval
Journal/Book: Online Cdrom Review. 1999; 23: Woodside, Hinksey Hill, Oxford, England Ox1 5Au. Learned Information Ltd. 11-18.
Abstract: Nowadays, applications dealing with information extracted from images are commonplace. The widespread use of multimedia information (images, video, audio etc.) makes necessary applications capable of storing, and therefore retrieving, it. Information extracted from images is usually complex and high dimensional. The extraction of non-textual low-level indexing features from images is now a research field, and this process principally suffers because of the computational cost of the high dimensionality of those features. A new way to classify and match low-level features extracted from images, for retrieval purposes, is presented in this paper. M-tree and R-tree structures are used, as well as an incremental version of the k-means classification algorithm. This set of algorithms is used to solve the problem of low performance when retrieving previously catalogued images.
Note: Article Encinas J, Univ Carlos III Madrid, Informat Technol Grp, Dept Comp Sci, Madrid, SPAIN