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Proceedings Paper

Experience with CANDID: comparison algorithm for navigating digital image databases
Author(s): Patrick M. Kelly; T. Michael Cannon
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Paper Abstract

This paper presents results from our experience with CANDID (comparison algorithm for navigating digital image databases), which was designed to facilitate image retrieval by content using a query-by-example methodology. A global signature describing the texture, shape, or color content is first computed for every image stored in a database, and a normalized similarity measure between probability density functions of feature vectors is used to match signatures. This method can be used to retrieve images from a database that are similar to a user-provided example image. Results for three test applications are included.

Paper Details

Date Published: 31 January 1995
PDF: 12 pages
Proc. SPIE 2368, 23rd AIPR Workshop: Image and Information Systems: Applications and Opportunities, (31 January 1995); doi: 10.1117/12.200807
Show Author Affiliations
Patrick M. Kelly, Los Alamos National Lab. (United States)
T. Michael Cannon, Los Alamos National Lab. (United States)


Published in SPIE Proceedings Vol. 2368:
23rd AIPR Workshop: Image and Information Systems: Applications and Opportunities
Peter J. Costianes, Editor(s)

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