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10 May 2012 Extracting edge histogram detector features from ground penetrating radar data without ground alignment
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When processing ground penetrating radar (GPR) data for the detection of subsurface objects it is common to align the data based on the location of the air-ground interface in order to eliminate the effects of antenna motion. This practice assumes that the ground is mostly flat and that variations in the measured ground locations are primarily due to antenna motion. In practice this assumption is often false so ground alignment will cause true ground contours to be flattened, potentially distorting signatures from subsurface objects. In this paper we investigate extracting edge histogram descriptor (EHD) features from GPR data with varying degrees of alignment: unaligned, fully aligned and aligned only in the downtrack direction, where the effects of antenna motion are most prevalent. One problem with not performing ground alignment is that features generated from the ground surface or subsurface layers that follow the contour of the ground may cause false alarms. To address this problem we also consider employing background subtraction prior to feature extraction on aligned data, independent of the alignment method used for feature extraction. We compare the detection performance of algorithms using each of these feature extraction approaches.
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Joshua Wood, Joseph Wilson, and Jeremy Bolton "Extracting edge histogram detector features from ground penetrating radar data without ground alignment", Proc. SPIE 8357, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVII, 83571W (10 May 2012);

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