title: Automated vehicle detection in forward-looking infrared imagery.
abstract: 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.
authors.affiliation: US Army Research Laboratory, 2800 Powder Mill Road, Adelphi, Maryland 20783-1197, USA. sder@ragu.arl.mil
authors.forename: Sandor
authors.initials: S
authors.lastname: Der
authors.forename: Alex
authors.initials: A
authors.lastname: Chan
authors.forename: Nasser
authors.initials: N
authors.lastname: Nasrabadi
authors.forename: Heesung
authors.initials: H
authors.lastname: Kwon