Paper
4 May 2009 Two dimensional template matching method for buried object discrimination in GPR data
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Abstract
In this study discrimination of two different metallic object classes were studied, utilizing Ground Penetrating Radar (GPR). Feature sets of both classes have almost the same information for both Metal Detector (MD) and GPR data. There were no evident features those are easily discriminate classes. Background removal has been applied to original B-Scan data and then a normalization process was performed. Image thresholding was applied to segment B-Scan GPR images. So, main hyperbolic shape of buried object reflection was extracted and then a morphological process was performed optionally. Templates of each class representatives have been obtained and they were searched whether they match with true class or not. Two data sets were examined experimentally. Actually they were obtained in different time and burial for the same objects. Considerably high discrimination performance was obtained which was not possible by using individual Metal Detector data.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mehmet Sezgin "Two dimensional template matching method for buried object discrimination in GPR data", Proc. SPIE 7303, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV, 73032E (4 May 2009); https://doi.org/10.1117/12.818417
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Cited by 4 scholarly publications.
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KEYWORDS
General packet radio service

Metals

Sensors

Image segmentation

Infrared sensors

Magnetic sensors

Image processing

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