this presentation is on the applications of the image processing .

1. BY ASHWINI AWATARE

2. Contents:-
What is Image Processing ?
Steps followed in Image Processing .
Purpose of Image Processing.
Types of Image Processing .
Applications of Image Processing .
Applications in details .
Advantage and Limitations .
Resources .

3. What is Image Processing
Image processing is a method to convert an image
into digital form and perform some operations on it, in
order to get an enhanced image or to extract some
useful information from it.
Usually Image Processing system includes treating
images as two dimensional signals while applying
already set signal processing methods to them.

4. Images as functions

5. Image Processing :
An image defined in the "real world" is considered to be
a function of two real variables say x , y.
 Before going to processing an image, it is converted into
a digital form. Digitization includes sampling of image
and quantization of sampled values.
 After converting the image into bit information, processing
is performed.
 This processing technique may be,
*Image enhancement
* Image reconstruction
* Image compression

6. Image enhancement refers to accentuation, or
sharpening, of image features such as boundaries.
Image restoration is concerned with filtering the
observed image to minimize the effect of
degradations.
Image compression is concerned with minimizing the
number of bits required to represent an image.
* Text compression - CCITT GROUP3 & GROUP4
* Still image compression - JPEG
* Video image compression -MPEG

7. Image processing basically includes
the following three steps.
 Importing the image with optical scanner or by digital
photography.
Analyzing and manipulating the image which includes
data compression and image enhancement and
spotting patterns that are not to human eyes like
satellite photographs.
 Output is the last stage in which result can be altered
image or report that is based on image analysis.

8. Modern digital technology has made it possible to
manipulate multi-dimensional signals with systems
that range from simple digital circuits to advanced
parallel computers. The goal of this manipulation can
be divided into three categories:
* Image Processing image in -> image out
* Image Analysis image in -> measurements out
* Image Understanding image in -> high-level
description out
Image processing is referred to processing of a 2D
picture by a computer.

10. Purpose of Image processing
The purpose of image processing is divided into 5 groups.
They are:
 Visualization - Observe the objects that are not visible.
 Image sharpening and restoration - To create a better
image.
 Image retrieval - Seek for the image of interest.
 Measurement of pattern – Measures various objects in
an image.
 Image Recognition – Distinguish the objects in an
image.

11. Types of Image Processing
 There are two types of the Image Processing
1> Analog Image Processing
Analog Image Processing refers to the
alteration of image through electrical means.
The most common example is the television
image.

12. 2>Digital Image Processing :
In this case, digital computers are used to
process the image.
 The image will be converted to digital form using a
scanner – digitizer and then process it.
 It is defined as the subjecting numerical
representations of objects to a series of operations in
order to obtain a
desired result

13. Applications :
Computer Vision
Agricultural Applications
Face Detection
Medical Imaging
Microscope Image Processing
Raster Operation
Remote Sensing
 Non-destructive Evaluation

14. Applications
 Forensic Studies
 Textiles
 Material Science.
 Military
 Film industry
 Document processing
 Graphic arts
 Printing Industry

15. Document Handling

16. Signature Verification

17. Biometrics

18. Fingerprint Verification / Identification

19. Fingerprint Identification Research at UNR
Minutiae Matching
Delaunay Triangulation

20. Object Recognition Research
reference view 1 reference view 2
novel view recognized

21. Indexing into Databases
 Shape content

22. Interpretation of Aerial
Photography
Interpretation of aerial photography is a problem domain in both
computer vision and registration.

23. Autonomous Vehicles
 Land, Underwater, Space

24. Traffic Monitoring

25. Face Detection

26. Face Recognition

27. Face Detection/Recognition Research at
UNR

28. Facial Expression Recognition

29. Face Tracking

30. Hand Gesture Recognition
 Smart Human-Computer User Interfaces
 Sign Language Recognition

31. Human Activity Recognition

32. Medical Applications
 skin cancer breast cancer

33. Morphing

34. Inserting Artificial Objects into a Scene

35. Advantage
Advantages are as follows :
 you can remove unwanted objects, adjust exposure,
saturation, hue, levels, sharpness, and more.
Easy to manipulate.
 Compact storage.

36. Limitations :-
Limitations are as follows:
It's very costly depending on the system used, the
number of detectors purchased.
 Time consuming
 Lack of qualified professional

37. THANK YOU