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13 August 2002 Detection and classification of land mine targets in ground penetrating radar images
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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, Ray Kacelenga, and 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);

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