Progressive Search and Retrieval in Large Image Archives

Technological advances over the last several years have resulted in digital image and video libraries that, today, comprise tens of terabytes of on-line data. Due to the continued proliferation of image data, these libraries will grow significantly larger over the next few years. Consequently, the need f or databases that can effectively support storage, search, retrieval and transmissi on of this kind of nontraditional data will grow significantly. This paper describe s a project currently in progress at the IBM T.J. Watson Research Center under joint sponsorship by NASA, GSFC that explores some of these challenges. In this paper, we describe the architecture and implementation of a framework to perform content-based search of an image database where content is specified by the user at one or more of the three abstraction levels: pixel, feature and semantic. This framework incorporates a progressive methodology that allows a computationally efficient implementation of the image processing algorithms required in extracti ng the content during the query execution. As a result, this framework is more scalable to a large image archive.

By: L. Bergman, V. Castelli, J. Gerth, L. Knapp (IBM Boulder), C. -S. Li, R. Ryniker, B. Skelly (IBM Boulder), S. Carty (IBM Boulder), S. Gannamraju, S. Hutchins (IBM Boulder), I. Kontoyiannis (Stanford Univ.), J. Robinson, J. Sho udt (IBM Boulder) and J. Turek

Published in: RC20583 in 1996


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