10 June 2005 Side attack mine detection using near infra-red imagery
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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.
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John McElroy, Chris Hawkins, Paul D. Gader, James M. Keller, 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); doi: 10.1117/12.604190; https://doi.org/10.1117/12.604190
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