About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
Computer Vision and Image Understanding
Paper
Categorization of image databases for efficient retrieval using robust mixture decomposition
Abstract
In this paper, we present a robust mixture decomposition technique that automatically finds a compact representation of the data in terms of components. We apply it to the problem of organizing databases for efficient retrieval. The time taken for retrieval is an order of magnitude smaller than that of exhaustive search methods. We also compare our approach with other methods for decomposition that use traditional criteria such as Akaike, Schwarz, and minimum description length. We report results on the VisTex texture image database from the MIT Media Lab.