Side attack mine detection using near infra-red imagery

John McElroy; Chris Hawkins; Paul D. Gader; James M. Keller; Robert Luke

doi:10.1117/12.604190

10 June 2005 Side attack mine detection using near infra-red imagery

John McElroy, Chris Hawkins, Paul D. Gader, James M. Keller, Robert Luke

Proceedings Volume 5794, Detection and Remediation Technologies for Mines and Minelike Targets X; (2005) https://doi.org/10.1117/12.604190
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

Near Infra-Red (NIR) offers enhanced contrast of man-made objects against vegetation. Shape detection algorithms for identifying side-attack mines in sequences of NIR imagery are described. These algorithms use morphological representations of features of the object in a network that learns features and classification simultaneously. A training set was constructed using NIR images of side attack mines. Testing sets were constructed using pairs of sequences of NIR images. Each pair of sequences contains a sequence containing a side attack mine and another sequence of the same scene with no side attack mine. Testing results from these sequences are presented.

Citation Download Citation

John McElroy, Chris Hawkins, Paul D. Gader, James M. Keller, and Robert Luke "Side attack mine detection using near infra-red imagery", Proc. SPIE 5794, Detection and Remediation Technologies for Mines and Minelike Targets X, (10 June 2005); https://doi.org/10.1117/12.604190

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