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Proceedings Paper

LADAR And FLIR Based Sensor Fusion For Automatic Target Classification
Author(s): Fred Selzer; Dan Gutfinger
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Paper Abstract

The purpose of this report is to show results of automatic target classification and sensor fusion for forward looking infrared (FLIR) and Laser Radar sensors. The sensor fusion data base was acquired from the Naval Weapon Center and it consists of coregistered Laser RaDAR (range and reflectance image), FLIR (raw and preprocessed image) and TV. Using this data base we have developed techniques to extract relevant object edges from the FLIR and LADAR which are correlated to wireframe models. The resulting correlation coefficients from both the LADAR and FLIR are fused using either the Bayesian or the Dempster-Shafer combination method so as to provide a higher confidence target classifica-tion level output. Finally, to minimize the correlation process the wireframe models are modified to reflect target range (size of target) and target orientation which is extracted from the LADAR reflectance image.

Paper Details

Date Published: 5 January 1989
PDF: 11 pages
Proc. SPIE 1003, Sensor Fusion: Spatial Reasoning and Scene Interpretation, (5 January 1989); doi: 10.1117/12.948935
Show Author Affiliations
Fred Selzer, Ford Aerospace Corporation (United States)
Dan Gutfinger, Ford Aerospace Corporation (United States)


Published in SPIE Proceedings Vol. 1003:
Sensor Fusion: Spatial Reasoning and Scene Interpretation
Paul S. Schenker, Editor(s)

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