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30 April 2018 Sample spacing variations on the feature performance for subsurface object detection using handheld ground penetrating radar (Rising Researcher Presentation)
Brendan Alvey, Dominic K. C. Ho, Alina Zare
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Proceedings Volume 10628, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII; 106280U (2018) https://doi.org/10.1117/12.2303931
Event: SPIE Defense + Security, 2018, Orlando, FL, United States
Abstract
The use of handheld ground penetrating radar (GPR) for subsurface object detection often faces challenges coming from the human operator effect, antenna height variation and uneven data sample spacing. This paper investigates the artifact of uneven sample spacing on the performance of the features extracted from the handheld GPR, for the discrimination between targets and false alarms at the initial detection locations reported by a prescreener. The features we examined are the log Gabor and the Local Binary Pattern (LBP). They have been shown previously to be able to improve the detection performance in the absence of sample spacing artifact. The effect of the variation in the detection alarm location from the prescreener on the features will also be examined. The detection performance with and without sample spacing artifact and alarm location accuracy will be contrasted on a data set collected at a government test site.
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Brendan Alvey, Dominic K. C. Ho, and Alina Zare "Sample spacing variations on the feature performance for subsurface object detection using handheld ground penetrating radar (Rising Researcher Presentation)", Proc. SPIE 10628, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII, 106280U (30 April 2018); https://doi.org/10.1117/12.2303931
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KEYWORDS
Target detection
Land mines
Ground penetrating radar
Sensors
Feature extraction
Explosives
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