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- W1983707112 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." @default.
- W1983707112 created "2016-06-24" @default.
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- W1983707112 date "2002-08-12" @default.
- W1983707112 modified "2023-09-23" @default.
- W1983707112 title "<title>Detection and classification of land mine targets in ground penetrating radar images</title>" @default.
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- W1983707112 doi "https://doi.org/10.1117/12.479111" @default.
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