13 August 2002 Detection and classification of land mine targets in ground penetrating radar images
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Abstract
The present paper proposes image analysis methods for the detection and classification of landmine targets in images acquired using a ground penetrating radar sensor. The detection methodology initially employs a preprocessing step based on principal component analysis principles. The preprocessed image is further subjected to a multilevel density slicing operation to generate a map of iso-intensity contours in the image. Salient regions, that correspond to true targets as well as false-alarms in the image, are then segmented by establishing hierarchical intensity links within the framework of iso-intensity contours based on parent-to-child nodal relations. Features are proposed to classify mines and FAs based on size, shape, contrast, and texture of the segmented regions.
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Naga R. Mudigonda, Naga R. Mudigonda, Ray Kacelenga, Ray Kacelenga, David Palmer, David Palmer, } "Detection and classification of land mine targets in ground penetrating radar images", Proc. SPIE 4742, Detection and Remediation Technologies for Mines and Minelike Targets VII, (13 August 2002); doi: 10.1117/12.479111; https://doi.org/10.1117/12.479111
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