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Proceedings Paper

Signature prediction models for FLIR target recognition
Author(s): Vincent J. Velten
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Paper Abstract

Recognition of targets in flir imagery has been a goal of military weapon systems since the initial development of flir sensors. Reliable systems to automatically recognize targets in flir imagery have thus far eluded the combined efforts of the DOD services. Historical approaches have concentrated on adaptation of pattern recognition techniques from visible imagery (TV) target recognition. Recent research has suggested that consideration of target characteristics unique to IR imaging such as self emission due to thermal mass may lead to improved recognition performance. In order to effectively utilize these characteristics, predictive models are needed to establish the combination of viewing conditions and target states for which the target's thermal characteristics manifest themselves. This paper will focus upon the use of signature prediction models as a component of a recognition algorithm in the context of model-based vision (MBV).

Paper Details

Date Published: 1 November 1991
PDF: 10 pages
Proc. SPIE 10307, Automatic Object Recognition, 1030709 (1 November 1991); doi: 10.1117/12.2283650
Show Author Affiliations
Vincent J. Velten, Wright Research and Development Ctr. (United States)

Published in SPIE Proceedings Vol. 10307:
Automatic Object Recognition
Hatem N. Nasr, Editor(s)

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