| Image
Processing Articles
Index |
 |
| What
is a Binary Image? |
| Binary
images are images
whose pixels have
only two possible
intensity values.
They are normally
displayed as black
and white. Numerically,
the two values are
often 0 for black,
and either 1 or 255
for white. |
|
| Binary
images are often produced
by thresholding a
grayscale or color
image, in order to
separate an object
in the image from
the background. The
color of the object
(usually white) is
referred to as the
foreground color.
The rest (usually
black) is referred
to as the background
color. However, depending
on the image which
is to be thresholded,
this polarity might
be inverted, in which
case the object is
displayed with 0 and
the background is
with a non-zero value. |
|
| Some
morphological operators
assume a certain polarity
of the binary input
image so that if we
process an image with
inverse polarity the
operator will have
the opposite effect.
For example, if we
apply a closing operator
to a black text on
white background,
the text will be opened. |
|
| What
are Pixels? |
| In
order for any digital
computer processing
to be carried out
on an image, it must
first be stored within
the computer in a
suitable form that
can be manipulated
by a computer program.
The most practical
way of doing this
is to divide the image
up into a collection
of discrete (and usually
small) cells, which
are known as pixels.
Most commonly, the
image is divided up
into a rectangular
grid of pixels, so
that each pixel is
itself a small rectangle.
Once this has been
done, each pixel is
given a pixel value
that represents the
color of that pixel.
It is assumed that
the whole pixel is
the same color, and
so any color variation
that did exist within
the area of the pixel
before the image was
discretized is lost.
However, if the area
of each pixel is very
small, then the discrete
nature of the image
is often not visible
to the human eye. |
|
| Other
pixel shapes and formations
can be used, most
notably the hexagonal
grid, in which each
pixel is a small hexagon.
This has some advantages
in image processing,
including the fact
that pixel connectivity
is less ambiguously
defined than with
a square grid, but
hexagonal grids are
not widely used. Part
of the reason is that
many image capture
systems (e.g. most
CCD cameras and scanners)
intrinsically discretize
the captured image
into a rectangular
grid in the first
instance. |
|
| What
are Intensity values? |
| Each
of the pixels that
represents an image
stored inside a computer
has a pixel value
which describes how
bright that pixel
is, and/or what color
it should be. In the
simplest case of binary
images, the pixel
value is a 1-bit number
indicating either
foreground or background.
For a grayscale images,
the pixel value is
a single number that
represents the brightness
of the pixel. The
most common pixel
format is the byte
image, where this
number is stored as
an 8-bit integer giving
a range of possible
values from 0 to 255.
Typically zero is
taken to be black,
and 255 is taken to
be white. Values in
between make up the
different shades of
gray. |
|
| To
represent color images,
separate red, green
and blue components
must be specified
for each pixel (assuming
an RGB colorspace),
and so the pixel `value'
is actually a vector
of three numbers.
Often the three different
components are stored
as three separate
`grayscale' images
known as color planes
(one for each of red,
green and blue), which
have to be recombined
when displaying or
processing. |
|
| Multi-spectral
images can contain
even more than three
components for each
pixel, and by extension
these are stored in
the same kind of way,
as a vector pixel
value, or as separate
color planes. |
|
| The
actual grayscale or
color component intensities
for each pixel may
not actually be stored
explicitly. Often,
all that is stored
for each pixel is
an index into a colormap
in which the actual
intensity or colors
can be looked up. |
|
| Although
simple 8-bit integers
or vectors of 8-bit
integers are the most
common sorts of pixel
values used, some
image formats support
different types of
value, for instance
32-bit signed integers
or floating point
values. Such values
are extremely useful
in image processing
as they allow processing
to be carried out
on the image where
the resulting pixel
values are not necessarily
8-bit integers. If
this approach is used
then it is usually
necessary to set up
a colormap which relates
particular ranges
of pixel values to
particular displayed
colors. |
|
| What
is meant by the Term
RGB? |
| It
is a useful fact that
the huge variety of
colors that can be
perceived by humans
can all be produced
simply by adding together
appropriate amounts
of red, blue and green
colors. These colors
are known as the primary
colors. Thus in most
image processing applications,
colors are represented
by specifying separate
intensity values for
red, green and blue
components. This representation
is commonly referred
to as RGB. |
|
| The
primary color phenomenon
results from the fact
that humans have three
different sorts of
color receptors in
their retinas which
are each most sensitive
to different visible
light wavelengths. |
|
| The
primary colors used
in painting (red,
yellow and blue) are
different. When paints
are mixed, the `addition'
of a new color paint
actually subtracts
wavelengths from the
reflected visible
light. |
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| C#
Sample Program: |
|
| Guidelines
for Use: |
| To
illustrate Conversion
of Color Image to
Grayscale image, we
start with a simple
image containing some
distinct artificial
objects(specifically
text) |
 |
|
| Now
we apply Grayscale
conversion to the
image to convert it
to Grayscale image. |
|
 |
|
| Now
we apply Binary conversion
to the image to convert
it to Binary image. |
|
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