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Proceedings Paper

Automatic detection and tracking of reappearing targets in forward-looking infrared imagery
Author(s): A. Bal; M. S. Alam
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Paper Abstract

Target detection and tracking algorithms deal with the recognition of a variety of target images obtained from a multitude of sensor types, such as forward-looking infrared (FLIR), synthetic aperture radar and laser radar.1,2 Temporary disappearance and then reappearance of the target(s) in the field-of-view may be encountered during the tracking processes. To accommodate this problem, training based techniques have been developed using combination of two techniques; tuned basis functions (TBF) and correlation based template matching (TM) techniques. The TBFs are used to detect possible tentative target images. The detected candidate target images are then introduced into the second algorithm, called clutter rejection module, to determine the target reentering frame and location of the target. The performance of the proposed TBF-TM based reappeared target detection and tracking algorithm has been tested using real-world forward looking infrared video sequences.

Paper Details

Date Published: 20 February 2006
PDF: 6 pages
Proc. SPIE 6064, Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning, 60640K (20 February 2006); doi: 10.1117/12.643549
Show Author Affiliations
A. Bal, Univ. of South Alabama (United States)
M. S. Alam, Univ. of South Alabama (United States)

Published in SPIE Proceedings Vol. 6064:
Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning
Nasser M. Nasrabadi; Edward R. Dougherty; Jaakko T. Astola; Syed A. Rizvi; Karen O. Egiazarian, Editor(s)

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