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Proceedings Paper

Retrieval by content in symbolic-image databases
Author(s): Aya Soffer; Hanan Samet
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Paper Abstract

Two approaches for integrating images into the framework of a database management system are presented. The classification approach preprocesses all images and attaches a semantic classification and an associated certainty factor to each object found in the image. The abstraction approach describes each object in the image by using a vector consisting of the values of some of its features (e.g., shape, genus, etc.). The approaches differ in the way in which responses to queries that are based on image content are computed. In the classification approach, images are retrieved on the basis of whether or not they contain objects that have the same classification as query objects. In the abstraction approach, retrieval is on the basis of similarity of feature vector values of these objects. Both the pattern recognition and indexing aspects of the method are addressed for each approach. The emphasis is on extracting both contextual and spatial information from the raw images. Methods for storing and indexing symbolic images as tuples in a relation are presented for each approach. Indices are constructed for both the contextual and the spatial data. The user interface for a pictorial information system based on these two approaches is also presented.

Paper Details

Date Published: 13 March 1996
PDF: 12 pages
Proc. SPIE 2670, Storage and Retrieval for Still Image and Video Databases IV, (13 March 1996); doi: 10.1117/12.234791
Show Author Affiliations
Aya Soffer, Univ. of Maryland/Baltimore County and NASA Goddard Space Flight Ctr. (United States)
Hanan Samet, Univ. of Maryland/College Park (United States)

Published in SPIE Proceedings Vol. 2670:
Storage and Retrieval for Still Image and Video Databases IV
Ishwar K. Sethi; Ramesh C. Jain, Editor(s)

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