1. Abstract- Image processing is the
technique in which various operations
are carried out on images. It includes
mainly enhancement, detection, image
compression, etc. Image Processing has
various applications in various fields
including medical, astronomy, biometric,
etc. Image Processing is a vast field
which is used almost everywhere in
today’s world.
I. INTRODUCTION-
A single image speaks more than the
thousand words. Image processing is a
technique in which various operations
made on images. Every day, millions of
digital documents are produced by a
variety of devices and distributed by
newspapers, magazines, Websites and
television. In all these information
channels, images are a powerful tool for
communication. It is not difficult to use
computer graphics and image processing
techniques to manipulate images.
II. IMAGE PROCESSING-
Image processing is a study of
algorithms that takes image as input and
returns featured information. It mainly
includes display image. Printing of image,
editing of images, image enhancement,
image detection, image compression. It is
the manipulation of images by computers.
Image processing consists of three
types of operations that are-
1. Point operation-Image processing
is done pixel by pixel.
2. Neighborhood operations- operate
on a small group of adjacent pixels.
3. Reciprocal space operations- deal
with image-wide patterns and
characteristics.
Image processing consist of two types
that are analog image processing and
digital image processing
Analog Image Processing-
Analog image processing is the
image processing conducted on 2-
diamentional analog signals. The pictorial
representation of the data represented in
analog wave formats that can be named as
analog image. E.g. television broadcasting,
older days through the dish antenna
systems.
Digital image processing-
Digital image processing focuses on two
major tasks :( 1) Improvement of pictorial
information for human interpretation (2)
Processing of image data for storage,
transmission and representation for
autonomous machine perception
Advantages of Digital over Analog
Signal Processing:
1. The main advantage of digital signals
over analog signals is that the precise
signal level of the digital signal is not vital.
This means that digital signals are fairly
immune to the imperfections of real
electronic systems which tend to spoil
analog signals. As a result, digital CD's are
much more robust than analog LP's.
2. Codes are often used in the
transmission of information. These codes
can be used either as a means of keeping
the information secret or as a means of
breaking the information into pieces that
are manageable by the technology used to
transmit the code, e.g. The letters and
numbers to be sent by a Morse code are
coded into dots and dashes.
IMAGE PROCESSING
Presentation by:
Pradnya Patil Kirti Bajaj
2. 3. Digital signals can convey information
with greater noise immunity, because each
information component (byte etc) is
determined by the presence or absence of a
data bit (0 or one). Analog signals vary
continuously and their value is affected by
all levels of noise.
4. Digital signals can be processed by
digital circuit components, which are
cheap and easily produced in many
components on a single chip. Again, noise
propagation through the demodulation
system is minimized with digital
techniques.
5. Digital signals do not get corrupted by
noise etc. You are sending a series of
numbers that represent the signal of
interest (i.e. audio, video etc.)
6. Digital signals typically use less
bandwidth. This is just another way to say
you can cram more information (audio,
video) into the same space.
7. Digital can be encrypted so that only the
intended receiver can decode it (like pay
per view video, secure telephone etc.)
8. Enables transmission of signals over a
long distance.
9. Transmission is at a higher rate and with
a wider broadband width.
10. It is more secure.
11. It is also easier to translate human
audio and video signals and other
messages into machine language.
12. There is minimal electromagnetic
interference in digital technology.
13. It enables multi-directional
transmission simultaneously.
III.FEATURES PROVIDED BY
IMAGE PROCESSING
Image processing provides many features
some of them are as follows-
Face detection and recognition:
In this feature we can detect faces
present in image. It also recognize the face
by providing face image’s database..
Edge detection:
In the image edge area consist of high
frequency hence edge can be easily
detected to separate out each object from
one another.
Watermark:
Watermarks may be used to verify the
authenticity or integrity of the carrier
signal or to show the identity its owners.
Traditional watermarks may be applied to
visible media (like image or video)whereas
in digital watermarking the signal may be
audio, picture ,video, texts, or 3-D models.
IV. KEY STAGES IN IMAGE
PROCESSING
Image acquisition:
Image acquisition in image processing is
the retrieving an image from some source
usually hardware based. Image acquisition
is the first process in the image processing.
Image enhancement:
It improves the quality of image and useful
for image analysis .It is mainly exposes the
hidden information in the image
Image restoration:
Images taken with both digital camera and
conventional film cameras will pick up
noise from a variety of sources. Further
use of these images often requires that the
noise be removed for asthetic work or
3. marketing, or for practical purpose such as
computer vision.
Morphological processing:
Morphological image processing is a
collection of nonlinear operations related
to the shape and morphology of features in
an image. It is mainly useful for binary
images.
Image segmentation:
Image segmentation is the process in
which image is partitioned .the main goal
of segmentation is to simplify or change
the representation of an image into more
meaningful and easier to analyze. It is
typically used to locate object and
boundaries in image.
Object recognition:
Task is to finding and identifying objects
in an image or video sequence. Object is
recognized even it is in different sizes and
different views.
Representation and description:
Representation of image on the pixel graph
and description of its motion, color,
texture.
Image compression:
In this process memory space of image is
reduced. It provides space for other
images.
Color image processing:
In this technique, color is induced in
each pixel of image. There are thousands
of colors and its different intensities.
Image processing is divided into into three
types –
1. Low level process:
It takes input as image and output as
image. Examples: Noise removal,
image sharpening
2. Middle level process:
It takes image as input and output as
attribute.
Examples: Object recognition,
segmentation
3. High level process:
It takes image and touch and output as
3D graphic.
Examples: Scene understanding,
autonomous navigation
V. APPLICATION IN
DIFFERENT FIELDS
Astronomy:
Telescope can take images of very
distant objects.However, an incorrect
mirror made many of images
useless.Image processing techniques were
used to fix this
Artistic effects:
Artistic effects are used to make
images more visually appealing, to add
special effects and to make composite
images.
Medical:
MRI technique is mainly depending upon
Image processing. It produces high
resolution images without radiation
exposure and any known harmful effects
and without touching the patient. It is very
flexible and programmable. It is also used
to study various tissues and cancer
detection etc.
Agriculture:
Quality of product from farming is
mostly detected by comparing different
images of products.
Law enforcement:
Image processing techniques are used
extensively by law enforcers-
4. Number plate recognition for speed
cameras/automated toll systems,
Fingerprint recognition, Enhancement of
CCTV images.
Target recognition:
For focusing on target in image, it is useful
for the defence systems.
Night vision cameras:
This enables us to see in dark. Mainly in
defence system it is used to recognise the
location of attackers.
Psychology:
In psychology, it is used to detect whether
the person is lying or not.
Robotics:
Image processing is used to 3D human
movement modelling.
Autonomous cars:
Autonomous vehicles sense their
surrounding with RADAR or GPS like
system and computer vision and advanced
control system interpret sensory
information to identify appropriate
navigation paths as well as obstacles and
relevant signals.
Biometrics:
Image processing is used in biometrics to
detect person’s fingerprints, face
recognition, eye tracing, and signature.
Traffic management:
With the help of open cv, we are able to
count cars passing through the particular
area. With the help of this information we
can manage the traffic.
VI. SECURITY BY IMAGE
PROCESSING
In today’s growing world of growing
technology security is of utmost concern.
With the increase in cyber-crime ,
providing only network security is not
sufficient .Security provided to images like
blue print of company projects, secret
images of concern to the army or of
company’s interest, using image
steganography and stitching is
beneficial.as the text message is difficult to
find. More over since the secret image is
broken down into parts and then sent to the
receiver. This makes it difficult for the
trespassers to get access to all the parts of
the image at once. Thus increasing the
security to a much needed higher level.
This makes it becomes highly difficult for
the intruder to detect and decode the
document. There is no limitation on the
image format that can be used right from
.bmp to .giff image can be used. It can be
grey scale or colored images.
VII. CONCLUSION
Image processing is important topic today.
By image processing we do many things
by using the vision system. It has tight
relationship with other science branches.
Image processing gives us the new vision
towards surrounding. We can get money,
fun, humanity from ‘Image Processing’. It
leads you to design your work more
efficiently. It also provides security with
the help of image processing.
VIII. REFERENCES
1) www.youtube.com/watch?v=fvlEU
y_Zpk
2) Digital Image Processing:
Introduction -Brian Mac Namee
3) Image Processing Lecture 1
Introduction and Application-
Gaurav Gupta,Shobhit Niranjan
4) Digital Image Processing- C. A.
Bouman.
