This document discusses image processing. It begins by defining image processing as the conversion of an image to digital form and performing operations to enhance the image or extract useful information. The main steps are importing, analyzing/manipulating, and outputting the image. Types of image processing include analog and digital. Applications include computer vision, medical imaging, and document processing. Advantages include manipulation and compact storage, while limitations include cost, time consumption, and lack of professionals. The document provides details on several image processing techniques and applications.

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