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Proceedings Paper

Location hashing: an efficient indexing method for locating object queries in image databases
Author(s): Tanveer F. Syeda-Mahmood
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Paper Abstract

Queries referring to content embedded within images are an essential component of content-based search, browse, or summarize operations in image databases. Localization of such queries under changes in appearance, occlusions and background clutter, is a difficult problem, for which current spatial access structures in databases are not suitable. In this paper, we present a new method of indexing image databases, called location hashing, that uses a special data structure, called the location hash tree, for organizing feature information from images of a database. Location hashing is based on the principle of geometric hashing. It simultaneously determines the relevant images in the database, and the regions within them, which are most likely to contain 2D pattern query, without incurring a detailed search of either. The location hash tree being a red-black tree, allows for efficient search for candidate locations using pose-invariant feature information derived from the query.

Paper Details

Date Published: 17 December 1998
PDF: 13 pages
Proc. SPIE 3656, Storage and Retrieval for Image and Video Databases VII, (17 December 1998); doi: 10.1117/12.333856
Show Author Affiliations
Tanveer F. Syeda-Mahmood, IBM Almaden Research Ctr. (United States)

Published in SPIE Proceedings Vol. 3656:
Storage and Retrieval for Image and Video Databases VII
Minerva M. Yeung; Boon-Lock Yeo; Charles A. Bouman, Editor(s)

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