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Proceedings Paper

Automatic target recognition using Karhunen-Loeve transform-generated `eigenimages`
Author(s): Brian D. Singstock; Steven K. Rogers; Matthew Kabrisky; Dennis W. Ruck
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Paper Abstract

Most automatic target recognition (ATR) systems are based upon measuring a set of predetermined features someone has decided will separate the classes of targets from one another. However, this system requires the user to decide what features will work best. Maybe it would be best to look at the targets and decide what is different between them. This is the motivation behind taking the Karhunen-Loeve Transform (KLT) of the images. The KLT finds the most variance between the images thus leaving to the computer the decision of where the difference between the targets lies. In this paper, two approaches to feature generation for target classification of infrared images are addressed: a standard feature set approach, and a KLT approach. Each method is explained and results are included.

Paper Details

Date Published: 9 July 1992
PDF: 9 pages
Proc. SPIE 1699, Signal Processing, Sensor Fusion, and Target Recognition, (9 July 1992); doi: 10.1117/12.138230
Show Author Affiliations
Brian D. Singstock, Air Force Institute of Technology (United States)
Steven K. Rogers, Air Force Institute of Technology (United States)
Matthew Kabrisky, Air Force Institute of Technology (United States)
Dennis W. Ruck, Air Force Institute of Technology (United States)


Published in SPIE Proceedings Vol. 1699:
Signal Processing, Sensor Fusion, and Target Recognition
Vibeke Libby; Ivan Kadar, Editor(s)

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