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Proceedings Paper

Feature Analysis For Forward Looking Infrared (FLIR) Target Identification
Author(s): Yun-Kung J. Lin
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Paper Abstract

Feature analysis and classifier design toward real-time FLIR target identification are presented. After target candidates of military vehicles are segmented in a low resolution FLIR scenario, 1 a set of 17 features is extracted from these target areas in a single pass. These features consist of two optical intensity features, nine geometry features as well as six texture features. Five types of target candidates are examined in this study. They are tanks, APC's, jeeps, burning hulks, and other nontargets such as noise regions. A simple tree classifier is designed that is based on the manual interpretation of feature distribution among target categories at each nonterminal node of the tree classifier. The approach of feature extraction and classifier design has been applied to FLIR imagery provided by the U.S. Army Night Vision Laboratory and has shown promising results.

Paper Details

Date Published: 8 March 1982
PDF: 5 pages
Proc. SPIE 0302, Infrared Technology for Target Detection and Classification, (8 March 1982); doi: 10.1117/12.932638
Show Author Affiliations
Yun-Kung J. Lin, Harris Corporation (United States)

Published in SPIE Proceedings Vol. 0302:
Infrared Technology for Target Detection and Classification
Pat M. Narendra, Editor(s)

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