Feature-based detection of landmines in infrared images

Conference paper (2002)

Authors

WACM Messelink ImPhys/Quantitative Imaging
K Schutte ImPhys/Quantitative Imaging
A.M. Vossepoel ImPhys/Quantitative Imaging
F Cremer ImPhys/Quantitative Imaging
JGM Schavemaker External organisation
E den Breejen External organisation
Research Group
ImPhys/Quantitative Imaging
More Info
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Published Date

2002

Language

Undefined/Unknown

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Research Group

ImPhys/Quantitative Imaging

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.