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5226
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ha
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Ro
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Andrew
Abel
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1
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sta
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2
0
1
9
In
stit
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te o
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C
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p
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@
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m
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1.
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5219
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th
e
d
ata
ex
is
ts
an
d
t
h
e
s
ec
u
r
it
y
o
f
t
h
e
s
te
g
an
o
g
r
ap
h
y
s
y
s
te
m
r
elie
s
o
n
s
ec
r
ec
y
o
f
t
h
e
d
ata
en
co
d
in
g
s
y
s
te
m
C
o
n
w
a
y
[
3
]
”.
I
m
ag
e
s
teg
a
n
o
g
r
ap
h
y
tec
h
n
i
q
u
es
ca
n
b
e
clas
s
i
f
ied
in
to
t
w
o
m
aj
o
r
ca
teg
o
r
ies,
s
p
atial
d
o
m
a
in
tech
n
iq
u
es
an
d
f
r
eq
u
e
n
c
y
d
o
m
ai
n
tec
h
n
iq
u
es.
I
n
s
p
atial
d
o
m
ai
n
tec
h
n
iq
u
es,
i
m
ag
e
p
ix
el
s
ar
e
m
a
n
ip
u
lated
to
s
to
r
e
th
e
s
ec
r
et
m
e
s
s
a
g
e,
w
h
il
e
in
f
r
eq
u
e
n
c
y
d
o
m
ain
tec
h
n
i
q
u
es,
th
e
i
m
a
g
e
is
f
ir
s
t
tr
a
n
s
f
o
r
m
ed
b
y
ap
p
l
y
i
n
g
a
tr
an
s
f
o
r
m
atio
n
li
k
e
a
d
is
cr
ete
w
a
v
elet
tr
an
s
f
o
r
m
,
an
d
t
h
en
a
n
e
m
b
ed
d
in
g
tec
h
n
iq
u
e
is
ap
p
lied
t
o
h
id
e
th
e
m
es
s
ag
e.
B
o
th
tec
h
n
iq
u
es
h
a
v
e
t
h
eir
o
w
n
ad
v
an
tag
e
s
a
n
d
d
is
ad
v
a
n
ta
g
es.
I
n
t
h
e
s
p
ati
al
d
o
m
ain
,
th
er
e
ar
e
a
n
u
m
b
er
o
f
d
if
f
er
e
n
t
ca
teg
o
r
ies,
in
cl
u
d
in
g
L
e
ast
Sig
n
i
f
ic
an
t
B
it
s
te
g
a
n
o
g
r
ap
h
y
,
p
i
x
el
v
alu
e
d
i
f
f
er
en
ci
n
g
s
teg
a
n
o
g
r
ap
h
y
,
m
ap
p
in
g
b
ase
d
s
teg
a
n
o
g
r
ap
h
y
,
an
d
p
alette
b
ased
s
teg
a
n
o
g
r
ap
h
y
[
4
]
.
I
n
t
h
is
p
ap
er
,
th
e
L
ea
s
t
Sig
n
i
f
ica
n
t
B
it
(
L
SB
)
tec
h
n
iq
u
e
w
il
l
b
e
u
s
ed
f
o
r
i
m
a
g
e
s
te
g
an
o
g
r
ap
h
y
.
T
h
e
L
SB
tech
n
i
q
u
e
e
m
b
ed
s
s
ec
r
et
m
es
s
ag
e
s
in
to
th
e
co
v
er
i
m
ag
e
b
y
r
ep
lacin
g
t
h
e
least
s
ig
n
i
f
ic
an
t b
its
d
ir
ec
tl
y
.
Ho
w
e
v
er
,
o
n
ce
th
e
e
n
co
d
in
g
s
y
s
te
m
i
s
k
n
o
w
n
,
th
e
s
te
g
an
o
g
r
ap
h
y
s
y
s
te
m
is
ea
s
il
y
d
ef
ea
ted
.
T
h
er
ef
o
r
e,
th
e
d
ef
en
ce
o
f
t
h
e
ch
o
s
en
s
te
g
an
o
g
r
ap
h
y
tech
n
iq
u
e
ag
a
in
s
t
v
ar
io
u
s
attac
k
s
f
r
o
m
a
n
y
ad
v
er
s
ar
y
i
s
v
er
y
i
m
p
o
r
tan
t.
T
h
e
p
er
f
o
r
m
an
ce
o
f
v
ar
io
u
s
s
te
g
an
o
g
r
ap
h
y
m
e
th
o
d
s
ca
n
b
e
ev
al
u
ated
b
y
t
w
o
o
f
t
h
e
m
o
s
t
i
m
p
o
r
tan
t p
ar
a
m
eter
s
[
5
]
,
w
h
i
ch
ar
e
th
e
r
o
b
u
s
t
n
es
s
an
d
s
ec
u
r
it
y
o
f
t
h
e
s
te
g
o
i
m
a
g
e.
T
h
e
s
ec
u
r
it
y
f
ac
to
r
r
ef
er
s
to
th
e
s
ec
r
et
d
ata
b
ein
g
h
id
d
e
n
ev
e
n
af
ter
b
ein
g
tar
g
eted
b
y
v
ar
io
u
s
attac
k
s
.
I
f
t
h
e
s
ec
r
et
m
e
s
s
a
g
e
is
v
i
s
ib
le
i
n
t
h
e
co
v
er
i
m
ag
e,
its
f
i
le
f
o
r
m
at,
o
r
is
d
is
co
v
er
ed
d
u
r
in
g
s
teg
a
n
al
y
s
i
s
,
t
h
is
p
r
o
v
e
s
t
h
at
s
teg
an
o
g
r
ap
h
y
is
a
f
ail
u
r
e.
R
o
b
u
s
t
n
es
s
r
ep
r
esen
t
s
t
h
e
a
m
o
u
n
t
o
f
d
is
to
r
tio
n
th
at
a
d
ig
ital
co
v
er
ca
n
en
d
u
r
e
to
k
e
ep
th
e
s
ec
r
et
m
ess
a
g
e
s
a
f
e.
T
h
is
f
ac
to
r
in
c
lu
d
es
en
s
u
r
i
n
g
t
h
e
u
n
it
y
o
f
t
h
e
s
ec
r
et
m
es
s
ag
e
f
o
r
t
h
e
r
ec
ei
v
er
ev
e
n
if
th
e
s
te
g
o
i
m
ag
e
is
d
a
m
ag
e
d
b
y
a
n
y
at
tac
k
s
d
u
r
i
n
g
th
e
tr
an
s
m
i
s
s
io
n
p
h
ase
.
T
h
er
ef
o
r
e,
th
e
p
u
r
p
o
s
e
o
f
te
ch
n
iq
u
e
p
r
o
p
o
s
ed
in
th
is
p
ap
er
is
to
ac
h
ie
v
e
an
d
at
th
e
s
a
m
e
ti
m
e
i
m
p
r
o
v
e
th
e
r
o
b
u
s
t
n
ess
a
n
d
s
ec
u
r
it
y
o
f
th
e
s
teg
o
i
m
a
g
e.
T
h
e
aim
i
s
th
at
b
o
th
t
h
e
h
o
s
t
i
m
a
g
e
a
n
d
th
e
s
te
g
o
i
m
a
g
e
ca
n
n
o
t
b
e
d
if
f
er
e
n
tiated
b
y
a
n
y
d
i
f
f
er
e
n
ce
s
a
f
ter
u
n
d
er
g
o
in
g
C
h
i
-
s
q
u
ar
e
s
tati
s
tical
atta
ck
,
an
d
th
e
s
ec
r
et
m
es
s
ag
e
r
e
m
ai
n
s
i
n
its
o
r
ig
i
n
a
l f
o
r
m
.
A
n
u
m
b
er
o
f
tec
h
n
iq
u
es
t
h
at
h
av
e
b
ee
n
p
r
o
p
o
s
ed
u
s
i
n
g
t
h
e
L
SB
m
et
h
o
d
.
Z
h
an
g
an
d
T
an
g
[
6
]
p
r
o
p
o
s
ed
an
e
n
h
a
n
ce
m
en
t
o
v
e
r
L
ea
s
t
S
ig
n
i
f
ica
n
t
B
it
(
L
SB
)
tech
n
iq
u
e
th
at
s
elec
t
s
r
a
n
d
o
m
s
ets
o
f
p
i
x
els
w
it
h
th
e
h
elp
o
f
a
p
s
e
u
d
o
r
an
d
o
m
n
u
m
b
er
an
d
t
h
en
e
m
b
ed
s
n
b
its
in
ea
c
h
p
i
x
el
u
s
i
n
g
ad
d
itio
n
an
d
m
o
d
u
lar
d
iv
is
io
n
o
p
er
atio
n
s
.
T
h
e
len
g
th
o
f
th
e
b
it
s
tr
ea
m
o
f
t
h
e
e
m
b
ed
d
ed
m
ess
a
g
e
af
f
ec
ts
t
h
e
n
v
alu
e.
B
o
th
s
ec
u
r
it
y
an
d
ca
p
ac
it
y
ar
e
ad
d
r
ess
ed
.
A
d
d
itio
n
al
l
y
,
Ma
th
k
o
u
r
et
a
l
.
[
7
]
p
r
o
p
o
s
ed
a
s
p
ir
al
b
ased
L
SB
s
u
b
s
tit
u
tio
n
ap
p
r
o
ac
h
f
o
r
h
id
in
g
m
es
s
ag
e
s
in
i
m
a
g
es.
T
h
is
a
p
p
r
o
ac
h
is
b
ased
o
n
L
SB
s
u
b
s
t
itu
t
io
n
tec
h
n
iq
u
e
ap
p
lied
to
R
GB
co
lo
u
r
co
m
p
o
n
e
n
t
s
o
f
an
i
m
a
g
e.
T
h
e
i
m
a
g
e
is
d
iv
id
ed
i
n
to
m
a
n
y
i
m
ag
e
s
e
g
m
en
ts
a
n
d
d
if
f
er
en
t
p
r
o
ce
s
s
in
g
i
s
ap
p
lied
to
ea
ch
s
eg
m
e
n
t.
I
n
th
is
p
ap
er
w
e
p
r
o
p
o
s
e
to
co
m
b
i
n
e
th
e
K
n
ig
h
t
’
s
T
o
u
r
A
l
g
o
r
ith
m
w
it
h
th
e
L
SB
tech
n
iq
u
e
to
en
h
a
n
ce
t
h
e
s
teg
a
n
o
g
r
ap
h
y
m
et
h
o
d
.
I
n
th
e
Kn
i
g
h
t’
s
T
o
u
r
A
l
g
o
r
it
h
m
,
t
h
e
i
m
a
g
e
is
co
n
s
id
er
ed
j
u
s
t
lik
e
a
s
u
r
f
ac
e
o
f
a
ch
e
s
s
b
o
ar
d
.
A
cc
o
r
d
in
g
to
So
b
o
l
an
d
L
ev
itan
[
8
]
,
th
e
ad
v
an
tag
es
o
f
t
h
e
Kn
i
g
h
t
’
s
T
o
u
r
m
et
h
o
d
o
v
er
th
e
P
s
eu
d
o
-
R
an
d
o
m
N
u
m
b
er
Gen
er
ato
r
(
P
R
NG)
tec
h
n
iq
u
e
ar
e
t
h
at
it
i
s
a
s
el
f
-
d
ev
elo
p
ed
alg
o
r
ith
m
b
ased
o
n
th
e
Kn
i
g
h
t
’
s
T
o
u
r
m
a
th
e
m
atica
l
p
r
o
b
le
m
,
an
d
it
is
al
m
o
s
t
u
n
d
etec
tab
le
b
y
u
n
i
n
t
e
n
d
ed
o
r
u
n
a
u
t
h
o
r
is
ed
r
ec
eiv
er
s
.
As
d
is
c
u
s
s
ed
p
r
ev
io
u
s
l
y
,
it
is
i
m
p
o
r
tan
t
t
h
at
t
h
e
s
teg
a
n
o
g
r
ap
h
y
i
m
a
g
e
i
s
n
o
t
v
u
ln
er
ab
le
to
v
ar
io
u
s
attac
k
s
a
n
d
th
e
s
ec
r
et
m
e
s
s
a
g
e
co
n
v
e
y
i
n
g
is
n
o
t
v
is
ib
le
to
an
y
o
n
e.
Ho
w
e
v
er
,
m
a
n
y
p
r
ev
io
u
s
s
t
u
d
ies
[9
,
10]
h
av
e
id
e
n
ti
f
ied
th
at
s
te
g
a
n
o
g
r
ap
h
y
tech
n
iq
u
e
s
d
o
n
o
t
s
u
c
ce
s
s
f
u
l
l
y
h
id
e
th
e
s
ec
r
et
m
e
s
s
a
g
e
in
t
h
e
s
te
g
o
i
m
a
g
e
[
1
1
]
.
I
n
th
is
p
ap
er
,
th
e
C
h
i
-
s
q
u
ar
e
s
tat
is
tical
attac
k
is
u
s
ed
to
test
w
h
e
th
er
t
h
e
e
x
is
t
en
ce
o
f
t
h
e
s
ec
r
e
t
m
es
s
ag
e
i
n
t
h
e
s
te
g
o
i
m
a
g
e
c
a
n
b
e
ea
s
il
y
d
etec
ted
.
3.
P
RO
P
O
SE
D
F
RAM
E
WO
RK
I
n
th
is
p
ap
er
,
w
e
p
r
o
p
o
s
e
a
n
e
w
ap
p
r
o
ac
h
to
ac
h
iev
e
h
i
g
h
er
s
ec
u
r
it
y
b
y
u
s
in
g
t
h
e
L
SB
m
e
th
o
d
w
it
h
Kn
i
g
h
t
T
o
u
r
A
lg
o
r
it
h
m
.
T
h
e
t
w
o
m
ain
s
ta
g
es
ar
e
th
e
e
m
b
ed
d
in
g
s
tag
e
f
o
r
th
e
co
v
er
i
m
a
g
e
,
an
d
th
e
r
ec
eiv
i
n
g
s
tag
e
f
o
r
th
e
s
te
g
o
i
m
a
g
e.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
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2
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8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
9
,
No
.
6
,
Dec
em
b
er
2
0
1
9
:
5
2
1
8
-
5
2
2
6
5220
3
.
1
.
L
ea
s
t
s
ig
nifica
nt
bit
(
L
SB
)
L
ea
s
t
Sig
n
i
f
ica
n
t
B
it
(
L
SB
)
in
s
er
tio
n
i
s
o
n
e
o
f
t
h
e
m
o
s
t
p
o
p
u
lar
tech
n
iq
u
es
i
n
th
e
s
p
ati
al
-
d
o
m
ai
n
ca
teg
o
r
y
.
I
t is a
co
m
m
o
n
a
n
d
s
i
m
p
le
ap
p
r
o
ac
h
to
e
m
b
ed
a
s
e
cr
et
m
es
s
ag
e
i
n
a
h
o
s
t i
m
a
g
e.
T
h
e
L
SB
tech
n
iq
u
e
w
o
r
k
s
b
y
u
s
i
n
g
t
h
e
lea
s
t
s
i
g
n
i
f
ica
n
t
b
its
o
f
ea
c
h
p
i
x
el
in
o
n
e
i
m
a
g
e
to
h
id
e
t
h
e
m
o
s
t
s
i
g
n
i
f
ican
t
b
its
o
f
an
o
t
h
er
[
1
8
]
.
C
h
an
g
in
g
t
h
e
L
SB
o
f
a
p
i
x
el
w
i
ll
ca
u
s
e
s
o
m
e
s
m
all
ch
a
n
g
es
i
n
p
ix
el
in
te
n
s
it
y
,
h
o
w
e
v
er
,
th
ese
ch
a
n
g
es
ca
n
n
o
t
b
e
id
en
tif
ied
b
y
t
h
e
h
u
m
a
n
e
y
e
[
2
]
.
I
n
t
h
e
r
ec
eiv
i
n
g
s
ta
g
e,
th
e
d
ata
w
i
ll
b
e
ex
tr
ac
ted
an
d
d
ec
o
m
p
r
ess
ed
.
T
h
e
cip
h
er
te
x
t
i
s
t
h
e
n
d
ec
r
y
p
ted
to
r
e
v
e
al
th
e
e
m
b
ed
d
ed
m
e
s
s
a
g
e.
F
ig
u
r
e
1
ill
u
s
tr
ate
s
th
e
en
t
ir
e
g
e
n
er
al
f
r
a
m
e
w
o
r
k
p
r
o
ce
s
s
f
o
r
s
en
d
er
an
d
r
ec
eiv
e
r
.
Fig
u
r
e
1.
Gen
er
al
s
ta
g
e
f
o
r
s
e
n
d
er
an
d
r
ec
eiv
er
Fig
u
r
e
2.
Kn
ig
h
t
's
m
o
v
e
m
en
t
o
n
a
b
o
ar
d
3
.
2
.
K
nig
ht
t
o
ur
a
lg
o
rit
hm
T
h
e
“
Kn
i
g
h
t
T
o
u
r
”
alg
o
r
ith
m
w
as
f
ir
s
t
a
n
al
y
s
ed
b
y
E
u
ler
in
1
7
5
9
,
an
d
is
a
s
u
itab
le
tech
n
iq
u
e
to
f
o
r
m
u
late
t
h
e
s
eq
u
e
n
ce
o
f
t
h
e
s
ec
r
et
b
it
s
tr
ea
m
w
it
h
i
n
t
h
e
i
m
ag
e
p
i
x
els.
T
h
e
Kn
i
g
h
t
T
o
u
r
alg
o
r
ith
m
is
a
s
e
lf
-
d
ev
elo
p
ed
alg
o
r
ith
m
b
ased
o
n
th
e
k
n
i
g
h
t
to
u
r
m
at
h
e
m
atica
l
p
r
o
b
lem
[
6
]
.
I
t h
as t
h
e
ad
v
a
n
t
ag
e
o
v
er
t
h
e
P
s
eu
d
o
R
an
d
o
m
N
u
m
b
er
Gen
er
ato
r
(
P
R
NG)
tech
n
iq
u
e
i
n
th
at
it
ca
n
n
o
t
b
e
id
en
tif
ied
b
y
u
n
i
n
ten
d
ed
r
ec
eiv
er
s
.
T
h
e
Kn
ig
h
t
T
o
u
r
A
l
g
o
r
ith
m
d
i
v
id
es
t
h
e
ch
e
s
s
b
o
ar
d
in
to
b
lo
ck
s
.
I
n
t
h
e
n
×
n
c
h
ess
b
o
ar
d
,
th
e
k
n
i
g
h
t
tr
av
el
s
to
all
s
q
u
ar
es
o
n
ce
,
as
s
h
o
w
n
in
Fig
u
r
e
2
.
B
y
u
s
i
n
g
t
h
is
id
ea
,
h
i
g
h
s
ec
u
r
it
y
ca
n
b
e
ac
h
ie
v
e
d
in
s
te
g
a
n
o
g
r
ap
h
y
s
in
ce
t
h
e
s
ea
r
ch
s
p
ac
e
w
ill
b
e
s
ig
n
i
f
ica
n
tl
y
h
ig
h
w
h
e
th
e
r
o
r
n
o
t
th
e
th
e
s
tar
tin
g
s
q
u
ar
e
o
f
th
e
k
n
ig
h
t
’
s
m
o
v
e
i
s
k
n
o
w
n
[
1
3
]
.
-
Sen
d
er
s
id
e:
First
o
f
all,
th
e
p
lain
te
x
t
h
a
s
to
b
e
p
r
ep
ar
e
d
b
ef
o
r
eh
an
d
.
T
h
e
p
lain
tex
t
i
s
en
cr
y
p
ted
an
d
co
n
v
er
ted
to
b
in
ar
y
f
o
r
m
f
r
o
m
its
o
r
ig
i
n
al
ASC
I
I
v
al
u
e
.
T
h
e
i
m
a
g
e
p
ix
el
s
w
i
ll
b
e
u
s
ed
to
e
m
b
ed
th
e
e
n
cr
y
p
ted
m
ess
a
g
e.
Fro
m
h
er
e,
L
SB
is
u
s
ed
to
e
m
b
ed
th
e
s
ec
r
et
m
e
s
s
a
g
e
to
g
eth
er
w
it
h
t
h
e
co
v
er
i
m
a
g
e
b
y
r
ep
laci
n
g
t
h
e
lea
s
t
s
ig
n
i
f
ica
n
t
b
it
o
f
p
i
x
el
v
al
u
es
w
i
th
th
e
e
n
cr
y
p
ted
i
n
f
o
r
m
ati
o
n
b
its
.
T
h
u
s
,
a
s
teg
o
i
m
ag
e
i
s
cr
ea
ted
.
T
h
e
en
tire
p
r
o
ce
s
s
is
illu
s
tr
ated
in
Fi
g
u
r
e
3
.
-
R
ec
eiv
er
s
id
e:
T
h
e
s
teg
o
i
m
a
g
e
is
t
h
e
n
tr
a
n
s
m
itted
to
t
h
e
r
ec
eiv
er
.
T
h
e
r
ec
eiv
er
r
ec
ei
v
es
th
e
s
te
g
o
k
e
y
a
n
d
th
e
e
x
tr
ac
ti
n
g
al
g
o
r
ith
m
to
d
ec
o
d
e
th
e
i
m
a
g
e.
T
h
e
p
ix
e
l
b
i
n
ar
y
v
alu
e
s
ar
e
u
s
ed
w
it
h
t
h
e
L
SB
d
ec
o
d
er
to
s
ep
ar
ate
th
e
en
cr
y
p
ted
d
ata
f
r
o
m
t
h
e
i
m
a
g
e
p
i
x
el
v
al
u
es.
T
h
e
e
x
tr
ac
ti
n
g
alg
o
r
it
h
m
i
s
u
s
e
d
to
d
ec
r
y
p
t
th
e
d
ata
to
r
ev
ea
l th
e
h
id
d
en
m
es
s
ag
e.
T
h
e
p
r
o
ce
s
s
is
s
h
o
w
n
in
Fig
u
r
e
4
.
-
E
m
b
ed
d
ed
in
g
s
tag
e
:
T
h
e
e
m
b
ed
d
in
g
s
tag
e,
s
h
o
w
n
in
F
i
g
u
r
e
5
is
t
h
e
m
o
s
t
i
m
p
o
r
tan
t
p
ar
t
o
f
t
h
e
p
r
o
ce
s
s
.
T
h
is
d
eter
m
in
e
s
w
h
ich
o
r
d
er
th
e
i
m
ag
e
p
i
x
els
w
i
ll
b
e
alter
ed
w
it
h
th
e
s
ec
r
et
m
e
s
s
a
g
e.
T
h
e
o
r
d
er
o
f
p
ix
el
s
to
b
e
ch
an
g
ed
is
d
eter
m
in
ed
b
y
u
s
in
g
t
h
e
K
n
i
g
h
t
T
o
u
r
A
l
g
o
r
ith
m
[
1
4
]
.
T
h
is
p
r
o
v
id
es
h
ig
h
er
s
ec
u
r
it
y
to
th
e
e
m
b
ed
d
ed
d
ata
as
o
n
l
y
th
e
s
en
d
er
an
d
r
ec
eiv
er
ca
n
d
eter
m
in
e
t
h
e
lo
ca
tio
n
o
f
it
s
in
it
ial
ch
o
s
e
n
p
ix
e
l
an
d
th
e
later
p
at
h
s
co
r
r
ec
tl
y
,
i
n
co
m
p
ar
is
o
n
to
th
e
P
s
e
u
d
o
R
an
d
o
m
N
u
m
b
er
Ge
n
er
ato
r
(
PR
NG)
tec
h
n
iq
u
e.
T
h
e
L
SB
tec
h
n
iq
u
e
is
th
e
n
u
s
ed
to
e
m
b
ed
t
h
e
m
e
s
s
a
g
e
i
n
to
th
e
co
v
er
i
m
a
g
e.
Fi
n
all
y
a
s
te
g
o
i
m
ag
e
i
s
cr
ea
ted
.
3
.
3
.
Appl
y
ing
k
n
ig
ht
t
o
ur
a
lg
o
rit
h
m
T
h
e
Kn
ig
h
t
T
o
u
r
A
lg
o
r
ith
m
f
i
r
s
tl
y
d
iv
id
es
t
h
e
ch
es
s
b
o
ar
d
i
n
to
4
x
4
b
lo
ck
s
.
Fo
u
r
g
r
o
u
p
s
o
f
th
e
f
o
u
r
s
q
u
ar
es
in
ea
ch
b
lo
ck
ar
e
n
a
m
ed
“Ri
g
h
t
Dia
m
o
n
d
”,
“L
e
f
t
Dia
m
o
n
d
”,
“Ri
g
h
t
Sq
u
ar
e”
a
n
d
“L
e
f
t
Sq
u
ar
e”
a
s
s
h
o
w
n
in
F
ig
u
r
e
6
[
1
3
]
.
T
h
e
alg
o
r
ith
m
w
ill
co
v
er
all
p
ix
els
i
f
t
h
e
s
ize
o
f
t
h
e
i
m
ag
e
i
s
d
iv
is
ib
le
b
y
4
.
Ho
w
e
v
er
,
ex
t
r
a
co
lu
m
n
s
o
r
r
o
w
s
w
h
ic
h
ar
e
less
t
h
a
n
4
w
il
l b
e
u
n
u
s
ab
le.
T
h
e
p
r
o
p
o
s
e
d
alg
o
r
ith
m
h
as t
h
e
f
o
llo
w
in
g
s
tep
s
:
a.
Div
id
e
th
e
i
m
a
g
e
’
s
w
id
t
h
an
d
h
eig
h
t b
y
f
o
u
r
b
y
i
g
n
o
r
in
g
th
e
ex
tr
a
p
ix
els.
b.
Div
id
e
th
e
i
m
a
g
e
i
n
to
4
x
4
p
ix
el
b
lo
ck
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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ep
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ll th
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h
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t
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m
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g
e.
Af
ter
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a
s
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eter
m
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v
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t
h
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L
SB
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h
n
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et
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Fig
u
r
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3
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Sen
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r
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Fig
u
r
e
4.
R
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p
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r
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Fig
u
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5
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m
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Fig
u
r
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6
.
Fo
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
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p
E
n
g
,
Vo
l.
9
,
No
.
6
,
Dec
em
b
er
2
0
1
9
:
5
2
1
8
-
5
2
2
6
5222
3
.
4
.
Appl
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L
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ap
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
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&
C
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p
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g
I
SS
N:
2
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8
8
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ig
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m
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ith
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ig
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u
r
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
9
,
No
.
6
,
Dec
em
b
er
2
0
1
9
:
5
2
1
8
-
5
2
2
6
5224
C
o
n
v
er
s
el
y
,
t
h
e
P
SNR
v
al
u
e
o
f
b
o
th
tech
n
iq
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e
s
ar
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al
m
o
s
t
th
e
s
a
m
e.
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ev
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[1
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S
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K.
He
m
a
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n
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[2
]
N.
F
.
Jo
h
n
s
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n
,
a
t
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l
.
,
“
Ex
p
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[3
]
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.
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1
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2
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.
[4
]
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.
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wa
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d
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[5
]
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.
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.
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u
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K.
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h
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se
,
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s:
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.
[6
]
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Zh
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J.
T
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,
“
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0
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[7
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[8
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3
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0
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m
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Iss
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l.
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2
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2
0
1
3
.
[1
1
]
K.
Ra
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2
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H.
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,
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S
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,
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Dig
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1
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[1
3
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lm
o
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“
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rse
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p
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.
[1
4
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,
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n
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p
.
2
5
1
-
2
6
0
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1
9
9
7
.
[1
5
]
V
.
L
.
Re
d
d
y
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D.
A
.
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ra
m
a
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y
a
m
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n
d
D.
P
.
Ch
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y
,
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Im
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le
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tatio
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f
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6
]
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.
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u
tu
b
,
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ix
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ies
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e
b
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telli
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n
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e
,
v
o
l.
2
,
no.
1
,
2
0
1
0
.
[1
7
]
C.
Kra
e
tze
r,
J.
Ditt
m
a
n
n
a
n
d
L
.
L
a
n
g
,
“
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ra
n
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re
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h
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rity,
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te
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ter
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.
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0
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0
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6
.
[1
8
]
Z.
Xin
p
e
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g
a
n
d
W
.
S
h
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o
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g
,
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tt
e
rn
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l.
2
5
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.
3
,
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p
.
3
3
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3
9
,
2
0
0
4
.
[1
9
]
A
.
H
.
T
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riq
,
A
.
Q.
M
a
h
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u
d
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n
d
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Ha
ss
a
n
,
“
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tes
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ro
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stn
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rp
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iq
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e
s,”
IEE
E
4
6
t
h
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id
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st
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y
mp
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0
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3
.
[2
0
]
M
.
Do
u
g
las
,
K.
Ba
il
e
y
a
n
d
M
.
L
e
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y
,
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A
n
o
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d
a
ta,”
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ia
T
o
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d
Ap
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7
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3
,
2
0
1
8
.
[2
1
]
H.
M
a
u
lan
a
a
n
d
E.
R
.
S
y
a
h
p
u
tr
a
,
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y
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2
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1
7
.
[2
2
]
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M
a
lt
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n
i
a
n
d
R.
Ca
p
p
e
ll
i,
“
Ad
v
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n
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s
in
F
in
g
e
rp
rin
t
M
o
d
e
li
n
g
,
”
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g
e
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n
d
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si
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n
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.
3
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p
.
2
5
8
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6
8
,
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0
0
9
.
[2
3
]
W
.
C,
T
.
S
a
n
d
G
.
V
,
“
I
m
a
g
e
q
u
a
li
ty
m
e
a
su
re
s
f
o
r
f
in
g
e
rp
rin
t
im
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g
e
e
n
h
a
n
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e
m
e
n
t,
”
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u
lt
ime
d
ia
Co
n
te
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t
Rep
re
se
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ta
ti
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n
,
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la
ss
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ica
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n
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n
d
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e
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u
rity,
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r
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rli
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rg
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p
p
.
2
1
5
-
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2
2
,
2
0
0
6
.
[2
4
]
R.
R
a
n
d
H.
K,
“
A
re
v
ie
w
o
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im
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g
e
e
n
h
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n
c
e
m
e
n
t
o
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f
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irec
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ters
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m
Un
ive
rs
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y
,
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o
u
rn
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l
o
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ien
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e
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y
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l.
7
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o
.
2
,
p
p
.
5
2
-
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7
,
2
0
1
1
.
[2
5
]
B.
M
.
A
a
n
d
G
.
S
.
H,
“
S
y
ste
m
a
ti
c
m
e
th
o
d
s
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o
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th
e
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o
m
p
u
tatio
n
o
f
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irec
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l
f
ield
s
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n
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sin
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lar
p
o
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ts
o
f
f
in
g
e
rp
rin
ts,
”
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tt
e
rn
An
a
lys
is
a
n
d
M
a
c
h
i
n
e
In
telli
g
e
n
c
e
,
IEE
E
T
ra
n
sa
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ti
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n
s
,
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l
.
2
4
,
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o
.
7
,
p
p
.
9
0
5
-
9
1
9
,
2
0
0
2
.
[2
6
]
S
.
“
A
n
a
u
to
m
a
ti
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f
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g
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rp
rin
t
c
las
sif
ic
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ti
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e
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se
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n
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lar
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o
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a
n
d
stru
c
t
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re
sh
a
p
e
o
f
o
rien
tatio
n
f
ield
s,” F
a
k
u
lt
i
S
a
in
s Ko
m
p
u
ter
d
a
n
S
istem
M
a
k
lu
m
a
t,
2
0
1
2
.
[2
7
]
B.
J.
L
,
C.
G
.
T
,
G
.
P
.
J,
C
.
R
a
n
d
W
.
C.
L
,
“
Ev
a
lu
a
ti
o
n
o
f
p
a
tt
e
rn
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las
sif
ier
s
f
o
r
f
in
g
e
rp
rin
t
a
n
d
OCR
a
p
p
li
c
a
ti
o
n
s,
”
Pa
tt
e
rn
Rec
o
g
n
it
io
n
,
v
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l
.
2
7
,
n
o
.
4
,
p
p
.
4
8
5
-
5
0
1
,
1
9
9
4
.
[2
8
]
J.
A
.
K,
P
.
S
a
n
d
H
.
L
,
“
A
m
u
l
ti
c
h
a
n
n
e
l
a
p
p
ro
a
c
h
to
f
in
g
e
rp
rin
t
c
las
sif
i
c
a
ti
o
n
,
”
Pa
tt
e
r
n
An
a
lys
is
a
n
d
M
a
c
h
i
n
e
In
telli
g
e
n
c
e
,
IEE
E
T
ra
n
s
a
c
ti
o
n
s
,
v
o
l.
2
1
,
no.
4
,
p
p
.
3
4
8
-
3
5
9
,
1
9
9
9
.
[2
9
]
J.
A
.
K,
H.
L
,
P
.
S
a
n
d
B.
R
,
“
A
n
id
e
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ti
ty
-
a
u
th
e
n
ti
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ti
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sy
ste
m
u
sin
g
f
in
g
e
rp
rin
ts,
”
Pro
c
e
e
d
in
g
s
o
f
t
h
e
IEE
E
,
v
o
l.
8
5
,
no.
9
,
p
p
.
1
3
6
5
-
1
3
8
8
,
1
9
9
7
.
[3
0
]
C.
A
a
n
d
G
.
S
,
“
A
fa
st
f
in
g
e
r
p
rin
t
im
a
g
e
e
n
h
a
n
c
e
m
e
n
t
a
lg
o
rit
h
m
u
sin
g
a
p
a
ra
b
o
li
c
m
a
sk
,
”
Co
mp
u
ter
s
a
n
d
El
e
c
trica
l
En
g
in
e
e
rin
g
,
v
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l
.
3
4
,
n
o
.
3
,
p
p
.
2
5
0
-
2
5
6
,
2
0
0
8
.
[3
1
]
H.
L
,
W
.
Y
a
n
d
J.
A
,
“
F
in
g
e
rp
ri
n
t
im
a
g
e
e
n
h
a
n
c
e
m
e
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t
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lg
o
rit
h
m
a
n
d
p
e
rf
o
rm
a
n
c
e
e
v
a
lu
a
ti
o
n
,
”
P
a
tt
e
rn
A
n
a
lys
is
a
n
d
M
a
c
h
i
n
e
In
telli
g
e
n
c
e
,
IEE
E
T
ra
n
sa
c
ti
o
n
s
,
v
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l.
2
0
,
n
o
.
8
,
p
p
.
7
7
7
-
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8
9
,
1
9
9
8
.
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[3
2
]
H.
M
.
F
,
“
Co
n
tras
t
f
in
g
e
rp
rin
t
e
n
h
a
n
c
e
m
e
n
t
b
a
se
d
o
n
h
isto
g
ra
m
e
q
u
a
li
z
a
ti
o
n
f
o
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o
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e
d
b
y
b
it
re
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u
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ti
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o
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v
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to
r
q
u
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n
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iza
ti
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n
,
”
Co
mp
u
ter
S
c
ien
c
e
a
n
d
Ne
two
rk
S
e
c
u
rity
,
v
o
l.
1
1
,
no.
5
,
p
p
.
1
1
6
-
1
2
3
,
2
0
1
1
.
[3
3
]
F
.
M
,
H.
J
a
n
d
X
.
J,
“
A
n
o
v
e
l
f
in
g
e
rp
rin
t
im
a
g
e
p
re
p
ro
c
e
ss
in
g
a
lg
o
rit
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m
,
”
Ap
p
li
e
d
me
c
h
a
n
ics
a
n
d
ma
ter
i
a
ls
,
v
o
l.
3
4
7
,
p
p
.
2
5
2
8
-
2
5
3
2
,
2
0
1
3
.
[3
4
]
K.
J.
S
a
n
d
K.
E.
K,
“
A
n
e
n
h
a
n
c
e
d
th
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n
n
i
n
g
A
lg
o
rit
h
m
u
sin
g
p
a
ra
ll
e
l
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ro
c
e
ss
in
g
,
”
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g
e
Pro
c
e
ss
in
g
,
v
o
l.
3
,
p
p
.
4
5
2
-
4
5
5
,
2
0
0
1
.
[3
5
]
Z.
J,
C.
F
a
n
d
G
.
J,
“
A
n
o
v
e
l
a
lg
o
rit
h
m
f
o
r
d
e
tec
ti
n
g
sin
g
u
lar
p
o
in
t
s
f
ro
m
f
in
g
e
rp
rin
t
im
a
g
e
s,”
IEE
E
T
ra
n
s.
Pa
tt
e
r
n
An
a
lys
is
a
n
d
M
a
c
h
i
n
e
In
tell
ig
e
n
c
e
,
v
o
l.
3
1
,
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o
.
7
,
p
p
.
1
2
3
9
-
1
2
5
0
,
2
0
0
9
.
[3
6
]
N.
F
.
Jo
h
n
s
o
n
,
a
t
a
l
.
,
“
Ex
p
l
o
rin
g
ste
g
a
n
o
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ra
p
h
y
:
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e
e
in
g
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e
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e
n
,
”
Co
mp
u
ter
,
v
o
l.
3
1
,
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o
.
2
,
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p
.
2
6
-
3
4
,
1
9
9
8
.
B
I
O
G
RAP
H
I
E
S
O
F
AUTH
O
RS
Ann
Nie
S
o
o
,
Cu
rre
n
t
P
o
siti
o
n
:
IT
Co
n
su
lt
a
n
t
f
o
r
Bu
sin
e
ss
In
tell
ig
e
n
c
e
S
o
f
t
w
a
re
.
Ed
u
c
a
ti
o
n
:
M
sc
.
Co
m
p
u
ter S
c
ien
c
e
(Un
i.
T
e
k
n
o
lo
g
i
M
a
la
y
sia
)
G
h
a
z
a
li
S
u
l
o
n
g
,
Cu
rre
n
t
P
o
siti
o
n
:
P
r
o
f
e
ss
o
r
a
t
Un
iv
e
rsiti
T
e
k
n
o
lo
g
i
M
a
lay
si
a
.
Ed
u
c
a
ti
o
n
:
P
h
d
i
n
Co
m
p
u
ter S
c
ien
c
e
,
W
a
les
Un
iv
e
r
sity
.
S
p
e
c
ializa
ti
o
n
:
Im
a
g
e
P
ro
c
e
s
sin
g
,
Bio
m
e
tri
c
s,
W
a
ter
m
a
rk
in
g
Ro
z
n
iza
Ali
,
Cu
rre
n
t
P
o
siti
o
n
:
S
e
n
io
r
L
e
c
tu
re
r,
Un
iv
e
rsiti
M
a
la
y
si
a
Tere
n
g
g
a
n
u
.
Hig
h
e
st E
d
u
c
a
ti
o
n
:
P
h
D
in
Co
m
p
u
ter
S
c
ien
c
e
,
S
t
irl
in
g
Un
iv
e
rsit
y
.
S
p
e
c
ializa
ti
o
n
:
M
a
c
h
in
e
L
e
a
rn
in
g
,
Im
a
g
e
P
ro
c
e
ss
in
g
,
P
a
tt
e
r
n
Re
c
o
g
n
it
i
o
n
And
r
e
w
Ab
e
l
,
Cu
rre
n
t
P
o
siti
o
n
:
L
e
c
tu
re
r
a
t
X
i'
a
n
Jia
o
to
n
g
-
L
i
v
e
rp
o
o
l
Un
iv
e
rsity
.
Hi
g
h
e
s
t
Ed
u
c
a
ti
o
n
:
P
h
D
in
C
o
m
p
u
ter
S
c
ien
c
e
,
S
ti
rli
n
g
Un
iv
e
rsity
.
S
p
e
c
ializa
ti
o
n
:
M
a
c
h
i
n
e
L
e
a
rn
in
g
,
A
rti
f
icia
l
In
telli
g
e
n
c
e
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