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Feature-based detection of landmines in infrared images

Attachments

Author: Messelink, W.A.C.M. · Schutte, K. · Vossepoel, A.M. · Cremer, F. · Schavemaker, J.G.M. · Breejen, E. den
Type:article
Date:2002
Publisher: SPIE
Place: Bellingham,WA
Institution: TNO Fysisch en Elektronisch Laboratorium
Source:Detection and Remediation Technechnologies for Mine and Minelike Targets VII, Apr. 2002, Orlando FL, USA, 108-119
series:
Proceedings of SPIE
Identifier: 209991
doi: doi:10.1117/12.479081
Keywords: Physics · Landmine detection · Infrared · Hough transform · Tophat filter · Feature selection

Abstract

High detection performance is required for an operational system for the detection of landmines. Humanitarian de-mining scenarios, combined with inherent difficulties of detecting landmines on an operational (vibration, motion, atmosphere) as well as a scenario level (clutter, soil type, terrain), result in high levels of false alarms for most sensors. To distinguish a landmine from background clutter one or more discriminating object features have to be found. The research described here focuses on finding and evaluating one or more features to distinguish disk-shaped landmines from background clutter in infrared images. These images were taken under controlled conditions, with homogenous soil types. Two methods are considered to acquire shape-based features in the infrared imagery. The first method uses a variation of the Hough transformation to find circular shaped objects. The second method uses the tophat filter with a disk-shaped structuring element. Furthermore, Mahalanobis and Fisher based classifiers are used to combine these features.