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Proceedings Paper

Two dimensional template matching method for buried object discrimination in GPR data
Author(s): Mehmet Sezgin
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Paper 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.

Paper Details

Date Published: 4 May 2009
PDF: 9 pages
Proc. SPIE 7303, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV, 73032E (4 May 2009); doi: 10.1117/12.818417
Show Author Affiliations
Mehmet Sezgin, TÜBİTAK Marmara Research Ctr. (Turkey)


Published in SPIE Proceedings Vol. 7303:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV
Russell S. Harmon; J. Thomas Broach; John H. Holloway, Editor(s)

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