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Proceedings Paper

Classification of items in a walk-through metal detector using time series of eigenvalues of the polarizability tensor
Author(s): Jarmo Kauppila; Timo Ala-Kleemola; Juho Vihonen; Juha Jylhä; Marja Ruotsalainen; Ari Järvi; Ari Visa
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Paper Abstract

During the last decade, the safety regulations of the airports have been set to a new level. As the number of passengers is constantly increasing, yet effective but quick security control at checkpoints sets great requirements to the 21st century security systems. In this paper, we shall introduce a novel metal detector concept that enables not only to detect but also to classify hidden items, though their orientation and accurate location are unknown. Our new prototype walk-through metal detector generates mutually orthogonal homogeneous magnetic fields so that the measured dipole moments allow classification of even the smallest of the items with high degree of accuracy in real-time. Invariant to different rotations of an object, the classification is based on eigenvalues of the polarizability tensor that incorporate information about the item (size, shape, orientation etc.); as a further novelty, we treat the eigenvalues as time series. In our laboratory settings, no assumptions concerning the typical place, where an item is likely situated, are made. In that case, 90 % of the dangerous and harmless items, including knives, guns, gun parts, belts etc. according to a security organisation, are correctly classified. Made misclassifications are explained by too similar electromagnetic properties of the items in question. The theoretical treatment and simulations are verified via empirical tests conducted using a robotic arm and our prototype system. In the future, the state-of-the-art system is likely to speed-up the security controls significantly with improved safety.

Paper Details

Date Published: 4 May 2009
PDF: 10 pages
Proc. SPIE 7303, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV, 73030P (4 May 2009); doi: 10.1117/12.818424
Show Author Affiliations
Jarmo Kauppila, Tampere Univ. of Technology (Finland)
Timo Ala-Kleemola, Tampere Univ. of Technology (Finland)
Juho Vihonen, Tampere Univ. of Technology (Finland)
Juha Jylhä, Tampere Univ. of Technology (Finland)
Marja Ruotsalainen, Tampere Univ. of Technology (Finland)
Ari Järvi, Rapiscan Systems, Inc. (Finland)
Ari Visa, Tampere Univ. of Technology (Finland)


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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