Improving reliability for classification of metallic objects using a WTMD portal

J Makkonen; Liam Marsh; J Vihonen; A. Järvi; David Armitage; A Visa; A J Peyton

doi:10.1088/0957-0233/26/10/105103

Improving reliability for classification of metallic objects using a WTMD portal

J Makkonen, Liam Marsh, J Vihonen, A. Järvi, David Armitage, A Visa, A J Peyton

EEE - Academic & Research

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper, a walk-through metal detection (WTMD) portal is used for classification of metallic objects. The classification is based on the inversion of the magnetic polarisability tensor (tensor) of the object. The nature of bias and noise components in the tensor are examined by using real walk-through data, and consequently, a novel classifier is introduced. Furthermore, a novel method for detecting poorly inverted tensors is presented, enabling self-diagnostics for the WTMD portal. Based on the results, the novel methods increase the accuracy of metal object classification and have the potential to improve the reliability of a WTMD system.

Original language	English
Article number	105103
Pages (from-to)	1-11
Number of pages	11
Journal	Measurement Science and Technology
Volume	26
Issue number	10
DOIs	https://doi.org/10.1088/0957-0233/26/10/105103
Publication status	Published - 26 Aug 2015

Keywords

classification (of information)
eigenvalues and eigenfunctions
metals
polarization

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10.1088/0957-0233/26/10/105103

Electromagnetic Sensing Group
Peyton, A. (PI), Fletcher, A. (Researcher), Daniels, D. (CoI), Conniffe, D. (PGR student), Podd, F. (PI), Davidson, J. (Researcher), Anderson, J. (Support team), Wilson, J. (Researcher), Marsh, L. (PI), O'Toole, M. (PI), Watson, S. (PGR student), Yin, W. (PI), Regan, A. (PGR student), Williams, K. (Researcher), Rana, S. (Researcher), Khalil, K. (PGR student), Hills, D. (PGR student), Whyte, C. (PGR student), Wang, C. (PGR student), Hodgskin-Brown, R. (PGR student), Dadkhahtehrani, F. (PGR student), Forster, S. (PGR student), Zhu, F. (PGR student), Yu, K. (PGR student), Xiong, L. (PGR student), Lu, T. (PGR student), Zhang, L. (PGR student), Lyu, R. (PGR student), Zhu, R. (PGR student), She, S. (PGR student), Meng, T. (PGR student), Pang, X. (PGR student), Zheng, X. (PGR student), Bai, X. (PGR student), Zou, X. (PGR student), Ding, Y. (PGR student), Shao, Y. (PGR student), Xia, Z. (PGR student) & Zhang, Z. (PGR student)
1/10/04 → …
Project: Research

Cite this

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title = "Improving reliability for classification of metallic objects using a WTMD portal",

abstract = "In this paper, a walk-through metal detection (WTMD) portal is used for classification of metallic objects. The classification is based on the inversion of the magnetic polarisability tensor (tensor) of the object. The nature of bias and noise components in the tensor are examined by using real walk-through data, and consequently, a novel classifier is introduced. Furthermore, a novel method for detecting poorly inverted tensors is presented, enabling self-diagnostics for the WTMD portal. Based on the results, the novel methods increase the accuracy of metal object classification and have the potential to improve the reliability of a WTMD system.",

keywords = "classification (of information), eigenvalues and eigenfunctions, metals, polarization",

author = "J Makkonen and Liam Marsh and J Vihonen and A. J{\"a}rvi and David Armitage and A Visa and Peyton, {A J}",

note = "bias;Eigenvalues;noise;Polarisability;WTMD;",

year = "2015",

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T1 - Improving reliability for classification of metallic objects using a WTMD portal

AU - Makkonen, J

AU - Marsh, Liam

AU - Vihonen, J

AU - Järvi, A.

AU - Armitage, David

AU - Visa, A

AU - Peyton, A J

N1 - bias;Eigenvalues;noise;Polarisability;WTMD;

PY - 2015/8/26

Y1 - 2015/8/26

N2 - In this paper, a walk-through metal detection (WTMD) portal is used for classification of metallic objects. The classification is based on the inversion of the magnetic polarisability tensor (tensor) of the object. The nature of bias and noise components in the tensor are examined by using real walk-through data, and consequently, a novel classifier is introduced. Furthermore, a novel method for detecting poorly inverted tensors is presented, enabling self-diagnostics for the WTMD portal. Based on the results, the novel methods increase the accuracy of metal object classification and have the potential to improve the reliability of a WTMD system.

AB - In this paper, a walk-through metal detection (WTMD) portal is used for classification of metallic objects. The classification is based on the inversion of the magnetic polarisability tensor (tensor) of the object. The nature of bias and noise components in the tensor are examined by using real walk-through data, and consequently, a novel classifier is introduced. Furthermore, a novel method for detecting poorly inverted tensors is presented, enabling self-diagnostics for the WTMD portal. Based on the results, the novel methods increase the accuracy of metal object classification and have the potential to improve the reliability of a WTMD system.

KW - classification (of information)

KW - eigenvalues and eigenfunctions

KW - metals

KW - polarization

U2 - 10.1088/0957-0233/26/10/105103

DO - 10.1088/0957-0233/26/10/105103

M3 - Article

SN - 1361-6501

VL - 26

SP - 1

EP - 11

JO - Measurement Science and Technology

JF - Measurement Science and Technology

IS - 10

M1 - 105103

ER -

Improving reliability for classification of metallic objects using a WTMD portal

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Keywords

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Electromagnetic Sensing Group

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