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Proceedings Paper

Image content engine (ICE): a system for fast image database searches
Author(s): James M. Brase; Douglas N. Poland; David W. Paglieroni; George F. Weinert; Charles W. Grant; Aseneth S. Lopez; Sergei Nikolaev
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Paper Abstract

The Image Content Engine (ICE) is being developed to provide cueing assistance to human image analysts faced with increasingly large and intractable amounts of image data. The ICE architecture includes user configurable feature extraction pipelines which produce intermediate feature vector and match surface files which can then be accessed by interactive relational queries. Application of the feature extraction algorithms to large collections of images may be extremely time consuming and is launched as a batch job on a Linux cluster. The query interface accesses only the intermediate files and returns candidate hits nearly instantaneously. Queries may be posed for individual objects or collections. The query interface prompts the user for feedback, and applies relevance feedback algorithms to revise the feature vector weighting and focus on relevant search results. Examples of feature extraction and both model-based and search-by-example queries are presented.

Paper Details

Date Published: 19 May 2005
PDF: 5 pages
Proc. SPIE 5781, Optics and Photonics in Global Homeland Security, (19 May 2005); doi: 10.1117/12.608828
Show Author Affiliations
James M. Brase, Lawrence Livermore National Lab. (United States)
Douglas N. Poland, Lawrence Livermore National Lab. (United States)
David W. Paglieroni, Lawrence Livermore National Lab. (United States)
George F. Weinert, Lawrence Livermore National Lab. (United States)
Charles W. Grant, Lawrence Livermore National Lab. (United States)
Aseneth S. Lopez, Lawrence Livermore National Lab. (United States)
Sergei Nikolaev, Lawrence Livermore National Lab. (United States)


Published in SPIE Proceedings Vol. 5781:
Optics and Photonics in Global Homeland Security
Theodore T. Saito, Editor(s)

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