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Proceedings Paper

ATC (automatic target cueing) algorithm evaluation
Author(s): Jim M. Gleason; James W. Sherman
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Paper Abstract

The high volume of satellite derived oceanographic data, and the relatively high level of skill associated with the detection of important features in multi-sensor oceanographic datasets, has necessitated automating the analysis process. Since 1983 the Naval Oceanographic and Atmospheric Research Laboratory (NOARL) at NASA's Stennis Space Center has been involved in a effort which transitions research in automated interpretive techniques to operational use. The NOARL image understanding system's basic philosophy is unique in its strong emphasis on integration of different artificial intelligence techniques, conventional image processing techniques, statistical techniques, and low level vision techniques, making use of the strengths of each technique to optimally achieve the ultimate goal; an object based map showing icons which relate to detected features in the oceanographic imagery. The present paper describes the approach implemented, discusses lessons learned in past development efforts, and explains the rationale for the future evolutionary course of the system.

Paper Details

Date Published: 1 April 1991
PDF: 2 pages
Proc. SPIE 1406, Image Understanding in the '90s: Building Systems that Work, (1 April 1991); doi: 10.1117/12.47981
Show Author Affiliations
Jim M. Gleason, Environmental Research Institute of Michigan (United States)
James W. Sherman, Environmental Research Institute of Michigan (United States)

Published in SPIE Proceedings Vol. 1406:
Image Understanding in the '90s: Building Systems that Work
Brian T. Mitchell, Editor(s)

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