Region processing of ground-penetrating radar and electromagnetic induction for handheld landmine detection

Citation data:

Proceedings of SPIE - The International Society for Optical Engineering, ISSN: 0277-786X, Vol: 5415, Issue: PART 2, Page: 933-944

Publication Year:
2004
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Citations 12
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Repository URL:
http://scholarsmine.mst.edu/ele_comeng_facwork/2217
DOI:
10.1117/12.544323
Author(s):
Joseph N. Wilson; Russell S. Harmon; J. Thomas Broach; Paul D. Gader; Dominic K. C. Ho; John H. Holloway, Jr.; Wen-Hsiung Lee; Ronald J. Stanley; Taylor C. Glenn
Publisher(s):
SPIE-Intl Soc Optical Eng; SPIE -- The International Society for Optical Engineering
Tags:
Materials Science; Physics and Astronomy; Computer Science; Mathematics; Engineering; Data Collection; Discrimination Techniques; Electromagnetic Induction; Landmine Detection; Algorithms; Calibration; Data Processing; Electromagnetic Waves; Mobile Robots; Nonbibliographic Retrieval Systems; Ground Penetrating Radar Systems; Data Collection; Discrimination Techniques; Electromagnetic Induction; Landmine Detection; Algorithms; Calibration; Data Processing; Electromagnetic Waves; Mobile Robots; Nonbibliographic Retrieval Systems; Ground Penetrating Radar Systems; Electrical and Computer Engineering
conference paper description
An analysis of the utility of region-based processing of Ground Penetrating Radar (GPR) and Electromagnetic Induction (EMI) is presented. Algorithms for re-sampling GPR data acquired over non-rectangular and non-regular grids are presented. Depth-dependent whitening is used to form GPR images as functions of depth bins. Shape, size, and contrast-based features are used to distinguish mines from non-mines. The processing is compared to point-wise processing of the same data. Comparisons are made to GPR data collected by machine and by humans. Evaluations are performed on calibration data, for which the ground truth is known to the algorithm developers, and blind data, for which the ground truth is not known to the algorithm developers.