Feature-based detection of land mines in infrared images

Wilhelmus A. C. M. Messelink; Klamer Schutte; Albert M. Vossepoel; Frank Cremer; John G. M. Schavemaker; Eric den Breejen

doi:10.1117/12.479081

13 August 2002 Feature-based detection of land mines in infrared images

Wilhelmus A. C. M. Messelink, Klamer Schutte, Albert M. Vossepoel, Frank Cremer, John G. M. Schavemaker, Eric den Breejen

Author Affiliations +

Proceedings Volume 4742, Detection and Remediation Technologies for Mines and Minelike Targets VII; (2002) https://doi.org/10.1117/12.479081
Event: AeroSense 2002, 2002, Orlando, FL, United States

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.

Citation Download Citation

Wilhelmus A. C. M. Messelink, Klamer Schutte, Albert M. Vossepoel, Frank Cremer, John G. M. Schavemaker, and Eric den Breejen "Feature-based detection of land mines in infrared images", Proc. SPIE 4742, Detection and Remediation Technologies for Mines and Minelike Targets VII, (13 August 2002); https://doi.org/10.1117/12.479081

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