| Image
Processing Articles
Index |
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| Background |
| The
XOR binary operation
takes two binary inputs
and outputs 0 only
when both the inputs
are same ( i.e. if
both the inputs are
0 and when both the
inputs are 1 ) and
else if both the inputs
are not the same then
it outputs 1. The
XNOR binary operator
is the complete inverse
of the XOR binary
operation. XNOR outputs
1 when both the inputs
are same, else it
produces 0. The functionality
of XOR and XNOR are
clarified by the help
of the truth tables: |
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| Understanding
XOR & XNOR Mathematically |
The
XORing of two images
is carried out by
performing XOR operation
to the corresponding
images of the two
images to produce
the output pixel value.
For instance, suppose
that we wish to XOR
the integers 167 and
211 together using
8-bit integers. 167
is 10100111 in binary
and 255 is 11010011.
XORing these together
in bitwise fashion,
we have 01110100 in
binary or 110 in decimal.
This is not at all
the only implementation
of this of the logical
operators rather you
can implement the
logical XORing and
XNORing using some
thresholding to transform
the digital image
data into the binary
format, or simply
by taking the 0 pixel
value as the logical
0 and the non-zero
pixel values as the
logical 1 value. |
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| General
Working |
| The
XOR and XNOR operations
are performed through
a single pass module
which during operation
passes through the
each pixel of each
image and calculates
the pixels of the
output image by doing
the respective operation
on the corresponding
pixels to calculate
the output pixels.
It is necessary to
have two images of
the identical size.
In the sample program,
if two images are
not identical in size,
then they are made
of the same size (
explained below).
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| Guidelines
for Use |
| We
can illustrate the
function of the XOR
operator using |
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| and |
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| The
images show a scene
with two objects,
one of which is common
in both the images,
and the other is not
so. We can use XOR
to compute the union
of the images, i.e.
highlighting all pixels
which represent an
object either in the
first or in the second
image, and not in
both the images. First,
we threshold the images,
since the process
is simplified by use
binary input. If we
XOR the resulting
images. |
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| and |
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| we
obtain applying XOR
operator on the image
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| and
we obtain applying
XNOR operator |
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| C#
Sample Program: |
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| The
algorithm is coded
in C# using unsafe
so the quality and
speed of the program
may not be affected.
The class BitmapData
is used to read and
process the pixels
in the image. This
is the speicality
of C# to provide such
a speed even on image
processing applications.
There is a set of
modules that are designed
to implement the algorithm.
The program expects
that the input images
are grayscaled. Then
it takes the BitmapData
objects of the two
input images. It determines
which image is bigger
in width as well as
in height. Then it
scales the smaller
image to acquire the
size of the bigger
image to make the
sizes of both the
images equal. Then
the algorithm calculates
the XORed image in
the single pass through
the image. The final
output is an image
showing the result
of the effect of XOR
operator on the two
input images which
is then displayed
on the screen in the
down most picture
box. |
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