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Proceedings Paper

Data modeling and feature extraction for image databases
Author(s): Uri Shaft; Raghu Ramakrishnan
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Paper Abstract

Current image retrieval systems have many important limitations. Many are specialized for a particular domain of images, and are not applicable to other image domains. The more general systems treat all images uniformly. Consequently, the power of their query facility is limited to color, texture, shape, and other features that ar common to all images, with no deeper understanding of the structure of a given image. Few systems have addressed the issue of scalability with respect to the size of the image collection and with respect to the underlying techniques. There are two communities that can contribute to image databases: computer vision and database systems. In this paper we focus on the database side of the issue. We consider how to design a database system that supports a rich class of content-based queries on image collections, scales with collection size, and easily incorporate future advances in computer vision. This paper outlines one approach, in the form of the design, implementation and testing of an image database system called PIQ.

Paper Details

Date Published: 1 November 1996
PDF: 13 pages
Proc. SPIE 2916, Multimedia Storage and Archiving Systems, (1 November 1996); doi: 10.1117/12.257280
Show Author Affiliations
Uri Shaft, Univ. of Wisconsin/Madison (United States)
Raghu Ramakrishnan, Univ. of Wisconsin/Madison (United States)

Published in SPIE Proceedings Vol. 2916:
Multimedia Storage and Archiving Systems
C.-C. Jay Kuo, Editor(s)

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