An Electromagnetic Imaging System

shootceaselessUrban and Civil

Nov 16, 2013 (3 years and 8 months ago)

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An
Electromagnetic Imaging System

for


Metallic Object Detection and
Classification


By

Abdalrahman Al
-
qubaa


A thesis submitted to the School of Electrical
,

Electronic &

Computer
Engineering

in partial fulfilment of the requirements for the degree of

Doctor of Philosophy




________________________________________


Faculty of Science, Agriculture and Engineering

Newcastle University,
December
2012

________________________________________




i


Abstract

Electromagnetic imaging currently

play
s
a vital role in various disciplines
,

from
engineering to medical applications

and is
based
up
on the
characteristics

of
e
lectromagnetic fields and
their interaction with the properties of materials
.
The
detection and characteri
s
ation of
metallic objects

which pose
a

threat to safety is of
great interest in relation
to
public and
homeland
securit
y

worldwide.

Inspections are
c
onducted under the prerequisite that
is

divest
ed of all metallic objects
. Th
e
s
e

inspection conditions are problematic in terms of the disruption of the
movement

of
people

and produce a soft target for terrorist attack
. Thus, there is a need for
a
new
gener
ation

of detection systems
and information technologies
which can provide
an
enhanced characterisation and discrimination capabilities.

This thesis proposes an automatic metallic object detection and classification system.
T
wo related topics

have been add
ressed
: to design
and
implement

a new metallic object
detection system
;

and
to

develop

an

appropriate signal processing algorithm to classify
the target
ed

signatures.

The new
detection
system
use
s

an array of sensors in
conjunction with pulsed excitation
.

The
contribution
s

of this
research can be
summarised

as follows: (1)
i
nvestigat
ing

the

possibility of using magneto
-
resistance
sensors for metallic object detection
;

(2)
e
valuat
ing

the proposed system by generating a
database consist
ing

of 12 real handguns

with more than 20 objects

used in daily life;
(3)

e
xtract
ed
features
from the system outcomes using four feature categories referring to
the objects


shape, material composition, time
-
frequency signal analysis and transient
pulse response
; and
(4
)
applyin
g two
classification methods to classify the objects
into

threats and non
-
threats
,

giving a successful
classification rate of more than
92
% using
the
feature
combination

and classification
framework

of

the new system.


The
study

concludes that
novel

magnetic field imaging

system and their signal
outputs

c
an

be used to

detect, identify and classify
metallic objects. In comparison with
conventional induction
-
based walk
-
through metal detectors, the magneto
-
resistance
sensor array
-
based system show
s

great

potential
for

object identification and
discrimination.
This novel
system design and signal processing achievement

may be
able
to produce significant improvement
s

in automatic
threat
object
detection and
classification

applications.