Image Processing Reference
In-Depth Information
(Transformation III) Perform the following transformation of the above image
H
in the k -direction (1D weighted minimum filter). Denote
an output image by
referring to
H
S
=
{
s ijk }
(Fig. 5.12 (c)).
z ) 2 ; 1
s ijk =min
z {
h ijz +( k
z
N
}
.
(5.4)
Then the following property holds true concerning an image
S
.
Property 5.4. A value of a nonzero voxel in an image
obtained by
Transformation III is equal to the square of the Euclidean distance from a
nonzero voxel to the nearest 0-voxel. This is ascertained easily as follows
[Saito93, Saito94a].
(Proof) From equation (5.2),
S
x ) 2 ; f ijk = 0 , 1
g ijk =min
x {
( i
x
L
}
(5.5)
= the squared distance to the closest 0-voxel in the same row as ( i, j, k ) .
By substituting Eq. (5.5) with Eq. (5.3), we obtain
x ) 2 ; f xyk = 0 , 1
y ) 2 ; 1
h ijk =min
y {
min
x {
( i
x
L
}
+( j
y
M
}
x ) 2 +( j
y ) 2 ; f xyk = 0 , 1
=min
y {
min
x {
( i
x
L ; 1
y
M
}
x ) 2 +( j
y ) 2 ; f xyk = 0 , 1
=min
( x,y ) {
( i
x
L ; 1
y
M
}
(5.6)
= the squared distance to the closest 0-voxel in the same plane as ( i, j, k ) .
By substituting the result to Eq. (5.4),
x ) 2 +( j
y ) 2 ;
s ijk =min
z {
min
( x,y ) {
( i
z ) 2 ; 1
f xyk = 0 , 1
x
L, 1
y
M
}
+( k
z
N
}
x ) 2 +( j
y ) 2 +( k
z ) 2 ;
z {
( x,y ) {
( i
=min
min
f xyk = 0 , 1
x
L, 1
y
M ; 1
z
N
}
x ) 2 +( j
y ) 2 +( k
z ) 2 ;
=min
( x,y,z ) {
( i
f xyk = 0 , 1
x
L, 1
y
M ; 1
z
N
}
.
(5.7)
Thus it is shown that an image
S
is the squared EDT of an image
F
.
If a voxel is not cubic but a parallelepiped, the above transformations
should be modified as follows: assume here that the ratio among the lengths
of three edges of a voxel is 1 ( i -direction): α ( j -direction): β ( k -direction).
Then, using the same notations as in the Transformations I
III,
(Transformation II') Use the following equation instead of Eq. (5.3).
y )) 2 ; 1
h ijk =min
y {
g iyk +( α ( j
y
M
}
.
(5.8)
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