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Applied Optics

Applied Optics


  • Vol. 43, Iss. 2 — Jan. 10, 2004
  • pp: 333–348

Automated vehicle detection in forward-looking infrared imagery

Sandor Der, Alex Chan, Nasser Nasrabadi, and Heesung Kwon  »View Author Affiliations

Applied Optics, Vol. 43, Issue 2, pp. 333-348 (2004)

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We describe an algorithm for the detection and clutter rejection of military vehicles in forward-looking infrared (FLIR) imagery. The detection algorithm is designed to be a prescreener that selects regions for further analysis and uses a spatial anomaly approach that looks for target-sized regions of the image that differ in texture, brightness, edge strength, or other spatial characteristics. The features are linearly combined to form a confidence image that is thresholded to find likely target locations. The clutter rejection portion uses target-specific information extracted from training samples to reduce the false alarms of the detector. The outputs of the clutter rejecter and detector are combined by a higher-level evidence integrator to improve performance over simple concatenation of the detector and clutter rejecter. The algorithm has been applied to a large number of FLIR imagery sets, and some of these results are presented here.

© 2004 Optical Society of America

OCIS Codes
(040.2480) Detectors : FLIR, forward-looking infrared
(100.2000) Image processing : Digital image processing
(100.5010) Image processing : Pattern recognition

Original Manuscript: June 25, 2003
Revised Manuscript: October 3, 2003
Published: January 10, 2004

Sandor Der, Alex Chan, Nasser Nasrabadi, and Heesung Kwon, "Automated vehicle detection in forward-looking infrared imagery," Appl. Opt. 43, 333-348 (2004)

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