DIGITAL IMAGE
PROCESSING
Prepared by
K.Indragandhi,AP(Sr.Gr.)/ECE
DIGITAL IMAGE
PROCESSING
Basic Relationships between Pixels
Neighbors of a Pixel
f(0,0) f(0,1) f(0,2) f(0,3) f(0,4) - - - - -
f(1,0) f(1,1) f(1,2) f(1,3) f(1,4) - - - - -
f(x,y) = f(2,0) f(2,1) f(2,2) f(2,3) f(2,4) - - - - -
f(3,0) f(3,1) f(3,2) f(3,3) f(3,4) - - - - -
I I I I I - - - - -
I I I I I - - - - -
Neighbors of a Pixel
 A Pixel p at coordinates ( x, y) has 4 horizontal and vertical neighbors.
 Their coordinates are given by:
(x+1, y) (x-1, y) (x, y+1) &
(x, y-1)
f(2,1) f(0,1) f(1,2)
f(1,0)
 This set of pixels is called the 4-neighbors of p denoted by N4(p).
 Each pixel is unit distance from ( x ,y).
f(0,0) f(0,1) f(0,2) f(0,3) f(0,4) - - - - -
f(1,0) f(1,1) f(1,2) f(1,3) f(1,4) - - - - -
f(x,y) = f(2,0) f(2,1) f(2,2) f(2,3) f(2,4) - - - - -
f(3,0) f(3,1) f(3,2) f(3,3) f(3,4) - - - - -
I I I I I - - - - -
I I I I I - - - - -
Neighbors of a Pixel
 A Pixel p at coordinates ( x, y) has 4 diagonal neighbors.
 Their coordinates are given by:
(x+1, y+1) (x+1, y-1) (x-1, y+1) &
(x-1, y-1)
f(2,2) f(2,0) f(0,2)
f(0,0)
 This set of pixels is called the diagonal-neighbors of p denoted by
ND(p).

f(0,0) f(0,1) f(0,2) f(0,3) f(0,4) - - - - -
f(1,0) f(1,1) f(1,2) f(1,3) f(1,4) - - - - -
f(x,y) = f(2,0) f(2,1) f(2,2) f(2,3) f(2,4) - - - - -
f(3,0) f(3,1) f(3,2) f(3,3) f(3,4) - - - - -
I I I I I - - - - -
I I I I I - - - - -
Adjacency, Connectivity
Adjacency: Two pixels are adjacent if they are neighbors and
their intensity level ‘V’ satisfy some specific criteria of
similarity.
e.g. V = {1}
V = { 0, 2}
Binary image = { 0, 1}
Gray scale image = { 0, 1, 2, ------, 255}
In binary images, 2 pixels are adjacent if they are neighbors &
have some intensity values either 0 or 1.
In gray scale, image contains more gray level values in range 0
to 255.
Adjacency, Connectivity
4-adjacency: Two pixels p and q with the values from set ‘V’
are 4-adjacent if q is in the set of N4(p).
e.g. V = { 0, 1}
1 1 2
1 1 0
1 0 1
p in RED color
q can be any value in GREEN color.
Adjacency, Connectivity
8-adjacency: Two pixels p and q with the values from set ‘V’
are 8-adjacent if q is in the set of N8(p).
e.g. V = { 1, 2}
0 1 1
0 2 0
0 0 1
p in RED color
q can be any value in GREEN color
Adjacency, Connectivity
m-adjacency: Two pixels p and q with the values from set ‘V’
are m-adjacent if
(i) q is in N4(p) OR
(ii) q is in ND(p) & the set N4(p) n N4(q) have no pixels
whose values are from ‘V’.
e.g. V = { 1 }
0 a 1 b 1 c
0 d 1 e 0 f
0 g 0 h 1 i
Adjacency, Connectivity
m-adjacency: Two pixels p and q with the values from set ‘V’
are m-adjacent if
(i) q is in N4(p)
e.g. V = { 1 }
(i) b & c
0 a 1 b 1 c
0 d 1 e 0 f
0 g 0 h 1 I
Adjacency, Connectivity
m-adjacency: Two pixels p and q with the values from set ‘V’
are m-adjacent if
(i) q is in N4(p)
e.g. V = { 1 }
(i) b & c
0 a 1 b 1 c
0 d 1 e 0 f
0 g 0 h 1 I
Soln: b & c are m-adjacent.
Adjacency, Connectivity
m-adjacency: Two pixels p and q with the values from set ‘V’
are m-adjacent if
(i) q is in N4(p)
e.g. V = { 1 }
(ii) b & e
0 a 1 b 1 c
0 d 1 e 0 f
0 g 0 h 1 I
Adjacency, Connectivity
m-adjacency: Two pixels p and q with the values from set ‘V’
are m-adjacent if
(i) q is in N4(p)
e.g. V = { 1 }
(ii) b & e
0 a 1 b 1 c
0 d 1 e 0 f
0 g 0 h 1 I
Soln: b & e are m-adjacent.
Adjacency, Connectivity
m-adjacency: Two pixels p and q with the values from set ‘V’
are m-adjacent if
(i) q is in N4(p) OR
e.g. V = { 1 }
(iii) e & i
0 a 1 b 1 c
0 d 1 e 0 f
0 g 0 h 1 i
Adjacency, Connectivity
m-adjacency: Two pixels p and q with the values from set ‘V’
are m-adjacent if
(i) q is in ND(p) & the set N4(p) n N4(q) have no pixels
whose values are from ‘V’.
e.g. V = { 1 }
(iii) e & i
0 a 1 b 1 c
0 d 1 e 0 f
0 g 0 h 1 I
Adjacency, Connectivity
m-adjacency: Two pixels p and q with the values from set ‘V’
are m-adjacent if
(i) q is in ND(p) & the set N4(p) n N4(q) have no pixels
whose values are from ‘V’.
e.g. V = { 1 }
(iii) e & i
0 a 1 b 1 c
0 d 1 e 0 f
0 g 0 h 1 I
Soln: e & i are m-adjacent.
Adjacency, Connectivity
m-adjacency: Two pixels p and q with the values from set ‘V’
are m-adjacent if
(i) q is in N4(p) OR
(ii) q is in ND(p) & the set N4(p) n N4(q) have no pixels
whose values are from ‘V’.
e.g. V = { 1 }
(iv) e & c
0 a 1 b 1 c
0 d 1 e 0 f
0 g 0 h 1 I
Adjacency, Connectivity
m-adjacency: Two pixels p and q with the values from set ‘V’
are m-adjacent if
(i) q is in N4(p) OR
(ii) q is in ND(p) & the set N4(p) n N4(q) have no pixels
whose values are from ‘V’.
e.g. V = { 1 }
(iv) e & c
0 a 1 b 1 c
0 d 1 e 0 f
0 g 0 h 1 I
Soln: e & c are NOT m-adjacent.
Adjacency, Connectivity
Connectivity: 2 pixels are said to be connected if their exists a path
between them.
Let ‘S’ represent subset of pixels in an image.
Two pixels p & q are said to be connected in ‘S’ if their exists a path
between them consisting entirely of pixels in ‘S’.
For any pixel p in S, the set of pixels that are connected to it in S is
called a connected component of S.
Paths
Paths: A path from pixel p with coordinate ( x, y)
with pixel q with coordinate ( s, t) is a sequence of
distinct sequence with coordinates (x0, y0), (x1, y1),
….., (xn, yn) where
(x, y) = (x0, y0)
& (s, t) = (xn, yn)
Closed path: (x0, y0) = (xn, yn)
Paths
Example # 1: Consider the image segment shown in figure.
Compute length of the shortest-4, shortest-8 & shortest-m paths
between pixels p & q where,
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-4 path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-4 path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-4 path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-4 path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-4 path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-4 path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
So, Path does not exist.
Paths
Example # 1:
Shortest-8 path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-8 path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-8 path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-8 path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-8 path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-8 path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
So, shortest-8 path = 4
Paths
Example # 1:
Shortest-m path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-m path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-m path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-m path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-m path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-m path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
Paths
Example # 1:
Shortest-m path:
V = {1, 2}.
4 2 3 2 q
3 3 1 3
2 3 2 2
p 2 1 2 3
So, shortest-m path = 5
Regions & Boundaries
Region: Let R be a subset of pixels in an image. Two regions Ri
and Rj are said to be adjacent if their union form a connected set.
Regions that are not adjacent are said to be disjoint.
We consider 4- and 8- adjacency when referring to regions.
Below regions are adjacent only if 8-adjacency is used.
1 1 1
1 0 1 Ri
0 1 0
0 0 1
1 1 1 Rj
1 1 1
Regions & Boundaries
Boundaries (border or contour): The boundary of a region
R is the set of points that are adjacent to points in the
compliment of R.
0 0 0 0 0
0 1 1 0 0
0 1 1 0 0
0 1 1 1 0
0 1 1 1 0
0 0 0 0 0
RED colored 1 is NOT a member of border if 4-connectivity is
used between region and background. It is if 8-connectivity is
used.
Example:
(1=2)
(3=4)
(1=5)
Distance Measures
Distance Measures: Distance between pixels p, q & z with
co-ordinates ( x, y), ( s, t) & ( v, w) resp. is given by:
a) D( p, q) ≥ 0 [ D( p, q) = 0 if p = q] …………..called
reflexivity
b) D( p, q) = D( q, p) .………….called
symmetry
c) D( p, z) ≤ D( p, q) + D( q, z) ..………….called
transmitivity
Euclidean distance between p & q is defined as-
De( p, q) = [( x- s)2
+ (y - t)2
]1/2
Distance Measures
City Block Distance: The D4 distance between p & q is
defined as
D4( p, q) = |x - s| + |y - t|
In this case, pixels having D4 distance from ( x, y) less than or
equal to some value r form a diamond centered at ( x, y).
2
2 1 2
2 1 0 1 2
2 1 2
2
Pixels with D4 distance ≤ 2 forms the following contour of
constant distance.
Distance Measures
Chess-Board Distance: The D8 distance between p & q is
defined as
D8( p, q) = max( |x - s| , |y - t| )
In this case, pixels having D8 distance from ( x, y) less than or
equal to some value r form a square centered at ( x, y).
2 2 2 2 2
2 1 1 1 2
2 1 0 1 2
2 1 1 1 2
2 2 2 2 2
Pixels with D8 distance ≤ 2 forms the following contour of
constant distance.
Set operations
Logical operations
 The AND operator is usually used to mask out
part of an image.
 Parts of another image can be added with a
logical OR operator.
Result of AND Result of OR
OR
pixelrelationships in image processing enhancement

pixelrelationships in image processing enhancement

  • 2.
  • 3.
  • 4.
    Neighbors of aPixel f(0,0) f(0,1) f(0,2) f(0,3) f(0,4) - - - - - f(1,0) f(1,1) f(1,2) f(1,3) f(1,4) - - - - - f(x,y) = f(2,0) f(2,1) f(2,2) f(2,3) f(2,4) - - - - - f(3,0) f(3,1) f(3,2) f(3,3) f(3,4) - - - - - I I I I I - - - - - I I I I I - - - - -
  • 5.
    Neighbors of aPixel  A Pixel p at coordinates ( x, y) has 4 horizontal and vertical neighbors.  Their coordinates are given by: (x+1, y) (x-1, y) (x, y+1) & (x, y-1) f(2,1) f(0,1) f(1,2) f(1,0)  This set of pixels is called the 4-neighbors of p denoted by N4(p).  Each pixel is unit distance from ( x ,y). f(0,0) f(0,1) f(0,2) f(0,3) f(0,4) - - - - - f(1,0) f(1,1) f(1,2) f(1,3) f(1,4) - - - - - f(x,y) = f(2,0) f(2,1) f(2,2) f(2,3) f(2,4) - - - - - f(3,0) f(3,1) f(3,2) f(3,3) f(3,4) - - - - - I I I I I - - - - - I I I I I - - - - -
  • 6.
    Neighbors of aPixel  A Pixel p at coordinates ( x, y) has 4 diagonal neighbors.  Their coordinates are given by: (x+1, y+1) (x+1, y-1) (x-1, y+1) & (x-1, y-1) f(2,2) f(2,0) f(0,2) f(0,0)  This set of pixels is called the diagonal-neighbors of p denoted by ND(p).  f(0,0) f(0,1) f(0,2) f(0,3) f(0,4) - - - - - f(1,0) f(1,1) f(1,2) f(1,3) f(1,4) - - - - - f(x,y) = f(2,0) f(2,1) f(2,2) f(2,3) f(2,4) - - - - - f(3,0) f(3,1) f(3,2) f(3,3) f(3,4) - - - - - I I I I I - - - - - I I I I I - - - - -
  • 7.
    Adjacency, Connectivity Adjacency: Twopixels are adjacent if they are neighbors and their intensity level ‘V’ satisfy some specific criteria of similarity. e.g. V = {1} V = { 0, 2} Binary image = { 0, 1} Gray scale image = { 0, 1, 2, ------, 255} In binary images, 2 pixels are adjacent if they are neighbors & have some intensity values either 0 or 1. In gray scale, image contains more gray level values in range 0 to 255.
  • 8.
    Adjacency, Connectivity 4-adjacency: Twopixels p and q with the values from set ‘V’ are 4-adjacent if q is in the set of N4(p). e.g. V = { 0, 1} 1 1 2 1 1 0 1 0 1 p in RED color q can be any value in GREEN color.
  • 9.
    Adjacency, Connectivity 8-adjacency: Twopixels p and q with the values from set ‘V’ are 8-adjacent if q is in the set of N8(p). e.g. V = { 1, 2} 0 1 1 0 2 0 0 0 1 p in RED color q can be any value in GREEN color
  • 10.
    Adjacency, Connectivity m-adjacency: Twopixels p and q with the values from set ‘V’ are m-adjacent if (i) q is in N4(p) OR (ii) q is in ND(p) & the set N4(p) n N4(q) have no pixels whose values are from ‘V’. e.g. V = { 1 } 0 a 1 b 1 c 0 d 1 e 0 f 0 g 0 h 1 i
  • 11.
    Adjacency, Connectivity m-adjacency: Twopixels p and q with the values from set ‘V’ are m-adjacent if (i) q is in N4(p) e.g. V = { 1 } (i) b & c 0 a 1 b 1 c 0 d 1 e 0 f 0 g 0 h 1 I
  • 12.
    Adjacency, Connectivity m-adjacency: Twopixels p and q with the values from set ‘V’ are m-adjacent if (i) q is in N4(p) e.g. V = { 1 } (i) b & c 0 a 1 b 1 c 0 d 1 e 0 f 0 g 0 h 1 I Soln: b & c are m-adjacent.
  • 13.
    Adjacency, Connectivity m-adjacency: Twopixels p and q with the values from set ‘V’ are m-adjacent if (i) q is in N4(p) e.g. V = { 1 } (ii) b & e 0 a 1 b 1 c 0 d 1 e 0 f 0 g 0 h 1 I
  • 14.
    Adjacency, Connectivity m-adjacency: Twopixels p and q with the values from set ‘V’ are m-adjacent if (i) q is in N4(p) e.g. V = { 1 } (ii) b & e 0 a 1 b 1 c 0 d 1 e 0 f 0 g 0 h 1 I Soln: b & e are m-adjacent.
  • 15.
    Adjacency, Connectivity m-adjacency: Twopixels p and q with the values from set ‘V’ are m-adjacent if (i) q is in N4(p) OR e.g. V = { 1 } (iii) e & i 0 a 1 b 1 c 0 d 1 e 0 f 0 g 0 h 1 i
  • 16.
    Adjacency, Connectivity m-adjacency: Twopixels p and q with the values from set ‘V’ are m-adjacent if (i) q is in ND(p) & the set N4(p) n N4(q) have no pixels whose values are from ‘V’. e.g. V = { 1 } (iii) e & i 0 a 1 b 1 c 0 d 1 e 0 f 0 g 0 h 1 I
  • 17.
    Adjacency, Connectivity m-adjacency: Twopixels p and q with the values from set ‘V’ are m-adjacent if (i) q is in ND(p) & the set N4(p) n N4(q) have no pixels whose values are from ‘V’. e.g. V = { 1 } (iii) e & i 0 a 1 b 1 c 0 d 1 e 0 f 0 g 0 h 1 I Soln: e & i are m-adjacent.
  • 18.
    Adjacency, Connectivity m-adjacency: Twopixels p and q with the values from set ‘V’ are m-adjacent if (i) q is in N4(p) OR (ii) q is in ND(p) & the set N4(p) n N4(q) have no pixels whose values are from ‘V’. e.g. V = { 1 } (iv) e & c 0 a 1 b 1 c 0 d 1 e 0 f 0 g 0 h 1 I
  • 19.
    Adjacency, Connectivity m-adjacency: Twopixels p and q with the values from set ‘V’ are m-adjacent if (i) q is in N4(p) OR (ii) q is in ND(p) & the set N4(p) n N4(q) have no pixels whose values are from ‘V’. e.g. V = { 1 } (iv) e & c 0 a 1 b 1 c 0 d 1 e 0 f 0 g 0 h 1 I Soln: e & c are NOT m-adjacent.
  • 20.
    Adjacency, Connectivity Connectivity: 2pixels are said to be connected if their exists a path between them. Let ‘S’ represent subset of pixels in an image. Two pixels p & q are said to be connected in ‘S’ if their exists a path between them consisting entirely of pixels in ‘S’. For any pixel p in S, the set of pixels that are connected to it in S is called a connected component of S.
  • 21.
    Paths Paths: A pathfrom pixel p with coordinate ( x, y) with pixel q with coordinate ( s, t) is a sequence of distinct sequence with coordinates (x0, y0), (x1, y1), ….., (xn, yn) where (x, y) = (x0, y0) & (s, t) = (xn, yn) Closed path: (x0, y0) = (xn, yn)
  • 22.
    Paths Example # 1:Consider the image segment shown in figure. Compute length of the shortest-4, shortest-8 & shortest-m paths between pixels p & q where, V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 23.
    Paths Example # 1: Shortest-4path: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 24.
    Paths Example # 1: Shortest-4path: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 25.
    Paths Example # 1: Shortest-4path: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 26.
    Paths Example # 1: Shortest-4path: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 27.
    Paths Example # 1: Shortest-4path: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 28.
    Paths Example # 1: Shortest-4path: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3 So, Path does not exist.
  • 29.
    Paths Example # 1: Shortest-8path: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 30.
    Paths Example # 1: Shortest-8path: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 31.
    Paths Example # 1: Shortest-8path: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 32.
    Paths Example # 1: Shortest-8path: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 33.
    Paths Example # 1: Shortest-8path: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 34.
    Paths Example # 1: Shortest-8path: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3 So, shortest-8 path = 4
  • 35.
    Paths Example # 1: Shortest-mpath: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 36.
    Paths Example # 1: Shortest-mpath: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 37.
    Paths Example # 1: Shortest-mpath: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 38.
    Paths Example # 1: Shortest-mpath: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 39.
    Paths Example # 1: Shortest-mpath: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 40.
    Paths Example # 1: Shortest-mpath: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3
  • 41.
    Paths Example # 1: Shortest-mpath: V = {1, 2}. 4 2 3 2 q 3 3 1 3 2 3 2 2 p 2 1 2 3 So, shortest-m path = 5
  • 42.
    Regions & Boundaries Region:Let R be a subset of pixels in an image. Two regions Ri and Rj are said to be adjacent if their union form a connected set. Regions that are not adjacent are said to be disjoint. We consider 4- and 8- adjacency when referring to regions. Below regions are adjacent only if 8-adjacency is used. 1 1 1 1 0 1 Ri 0 1 0 0 0 1 1 1 1 Rj 1 1 1
  • 43.
    Regions & Boundaries Boundaries(border or contour): The boundary of a region R is the set of points that are adjacent to points in the compliment of R. 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 0 1 1 1 0 0 1 1 1 0 0 0 0 0 0 RED colored 1 is NOT a member of border if 4-connectivity is used between region and background. It is if 8-connectivity is used.
  • 44.
  • 51.
  • 53.
  • 56.
  • 59.
    Distance Measures Distance Measures:Distance between pixels p, q & z with co-ordinates ( x, y), ( s, t) & ( v, w) resp. is given by: a) D( p, q) ≥ 0 [ D( p, q) = 0 if p = q] …………..called reflexivity b) D( p, q) = D( q, p) .………….called symmetry c) D( p, z) ≤ D( p, q) + D( q, z) ..………….called transmitivity Euclidean distance between p & q is defined as- De( p, q) = [( x- s)2 + (y - t)2 ]1/2
  • 60.
    Distance Measures City BlockDistance: The D4 distance between p & q is defined as D4( p, q) = |x - s| + |y - t| In this case, pixels having D4 distance from ( x, y) less than or equal to some value r form a diamond centered at ( x, y). 2 2 1 2 2 1 0 1 2 2 1 2 2 Pixels with D4 distance ≤ 2 forms the following contour of constant distance.
  • 61.
    Distance Measures Chess-Board Distance:The D8 distance between p & q is defined as D8( p, q) = max( |x - s| , |y - t| ) In this case, pixels having D8 distance from ( x, y) less than or equal to some value r form a square centered at ( x, y). 2 2 2 2 2 2 1 1 1 2 2 1 0 1 2 2 1 1 1 2 2 2 2 2 2 Pixels with D8 distance ≤ 2 forms the following contour of constant distance.
  • 62.
  • 63.
  • 64.
     The ANDoperator is usually used to mask out part of an image.
  • 65.
     Parts ofanother image can be added with a logical OR operator.
  • 66.
    Result of ANDResult of OR OR