Image processing fundamentals

Mr. A. B. Shinde
Assistant Professor,
Electronics Engineering,
P.V.P.I.T., Budhgaon
shindesir.pvp@gmail.com
Digital Image Processing
Fundamentals
1

What is Image ?
 An image is a spatial representation of a two-
dimensional or three-dimensional scene.
 An image is an array, or a matrix pixels (picture
elements) arranged in columns and rows.
2

What is Image Processing
One picture is worth more than thousands of words.6

 Interest in digital image processing methods stems from
two principal application areas:
1. Improvement of pictorial information for human
interpretation
2. Processing of image data for storage, transmission, and
representation for autonomous machine perception
WHY…..digital image processing…???
7

DIP Definition:
A Discipline in Which Both the Input and Output of a
Process are Images.
WHAT IS DIGITAL IMAGE PROCESSING?
ProcessImage Image
8

 An image may be defined as a two-dimensional function, f(x, y),
where x and y are spatial (plane) coordinates, and the
amplitude of f at any pair of coordinates (x,y) is called the
intensity or gray level of the image at that point.
 Digital Image:
When x, y and the intensity values of f are all finite, discrete
quantities, we call the image a digital image.
What Is Digital Image ?
( , )
( , ) ( , )
( , )
r x y
f x y g x y
b x y
 
 
 
  
The field of digital image processing refers to processing digital
images by means of a digital computer.
 Color Image:
9

An Image:
Discretizatio
n
Quantizatio
n
g(x , y)
g(i , j)
f(i , j) Digital Image
f(i0 , j0) : Picture Element, Image Element, Pel, Pixel
What Is Digital Image ?
10

Image
Processing Vision
Low-Level
Process Mid-Level
Process
High-Level
Process
• Reduce Noise
• Contrast Enhancement
• Image Sharpening
• Segmentation
• Classification
Making Sense of an
Ensemble of
Recognized Objects
Image Analysis
WHAT IS DIGITAL IMAGE PROCESSING?
11

 One of the first applications of digital images was in the newspaper
industry, when pictures were first sent by submarine cable between
London and New York.
 Introduction of the Bartlane cable picture transmission system in the
early 1920s reduced the time required to transport a picture across the
Atlantic from more than a week to less than three hours.
Origins of Digital Image Processing
A digital picture produced in
1921 from a coded tape by a
telegraph printer with special
type faces.
12

 Today, there is almost no area of technical endeavor that is
not impacted in some way by digital image processing.
 Gamma-Ray Imaging
 X-Ray Imaging
 Imaging in the Ultraviolet Band
 Imaging in the Visible and Infrared Bands
 Imaging in the Microwave Band
 Imaging in the Radio Band
Fields that Use Digital Image Processing
13

Gamma-Ray Imaging
 Major uses of imaging
based on gamma rays
include nuclear medicine.
 In nuclear medicine, the
approach is to inject a
patient with a radioactive
isotope that emits gamma
rays as it decays.
 Images are produced from
the emissions collected by
gamma ray detectors.
Bone scan PET
Cygnus loop Reactor valve14

X-Ray Imaging
Cygnus loop
PCB
Chest
X-Ray
Head CT
Angiogram
15

Applications and Research Topics
16

 Document Handling
17

 Signature Verification
18

 Biometrics
19

 Fingerprint Verification / Identification
20

 Object Recognition
21

 Target Recognition
Department of Defense (Army, Air force, Navy)
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

 Traffic Monitoring
26

 Face Detection
27

 Face Recognition
28

 Face Detection/Recognition Research
29

 Facial Expression Recognition
30

 Hand Gesture Recognition
Smart Human-Computer User Interfaces
Sign Language Recognition
31

 Human Activity Recognition
32

 Medical Applications
breast cancerskin cancer
33

 Morphing
34

 Inserting Artificial Objects into a Scene
35

Fundamental Steps in Digital Image Processing
36

37

Essential steps when processing digital images:
Acquisition
Enhancement
Restoration
Color image restoration
Wavelets
Morphological processing
Segmentation
Representation
Recognition
Outputs are
digital
images
Outputs are
attributes of the
image
38

 Image acquisition is the first process.
Generally, the image acquisition stage involves
preprocessing, such as scaling.
39

 Image enhancement is the process of manipulating an image
so that the result is more suitable than the original for a specific
application.
There is no general “theory” of image enhancement.
When an image is processed for visual interpretation, the
viewer is the ultimate judge of how well a particular method
works.
40

 Image Restoration is an area that also deals with improving the
appearance of an image.
However, unlike enhancement, which is subjective, image
restoration is objective, in the sense that restoration techniques
tend to be based on mathematical or probabilistic models of
image degradation.
41

 Color Image Processing is an area that has been
gaining in importance because of the significant
increase in the use of digital images over the Internet.
 Wavelets are the foundation for representing images
in various degrees of resolution.
42

 Compression, as the name implies, deals with
techniques for reducing the storage required to save
an image, or the bandwidth required to transmit it. This
is true particularly in uses of the Internet.
43

 Morphological processing deals with tools for
extracting image components that are useful in the
representation and description of shape.
 Segmentation procedures partition an image into its
constituent parts or objects.
A segmentation procedure brings the process a
long way toward successful solution of imaging
problems that require objects to be identified
individually.
In general, the more accurate the segmentation,
the more likely recognition is to succeed.
44

 Representation and description almost always follow the
output of a segmentation stage, which usually is raw pixel
data.
 Boundary representation is appropriate when the focus is on
external shape characteristics, such as corners and
inflections.
 Regional representation is appropriate when the focus is on
internal properties, such as texture or skeletal shape.
Description, also called feature selection, deals with
extracting attributes that result in some quantitative
information of interest or are basic for differentiating one
class of objects from another.
 Recognition is the process that assigns a label (e.g.,
“vehicle”) to an object based on its descriptors. Digital
image processing with the development of methods for
recognition of individual objects.
45

General Purpose Image Processing System
46

 Specialized image processing hardware usually
consists of the digitizer, plus hardware that performs
other primitive operations, such as an arithmetic logic
unit (ALU), that performs arithmetic and logical
operations in parallel on entire images.
 This type of hardware sometimes is called a front-end
subsystem, and its most distinguishing characteristic
is speed.
47

 The Computer in an image processing system is a
general-purpose computer and can range from a PC
to a supercomputer.
 In dedicated applications, sometimes custom
computers are used to achieve a required level of
performance, but our interest here is on general-
purpose image processing systems.
 In these systems, almost any well-equipped PC-type
machine is suitable for off-line image processing
tasks.
48

 Software for image processing consists of specialized
modules that perform specific tasks.
 More sophisticated software packages allow the
integration of those modules and general-purpose
software commands from at least one computer
language.
49

 Mass storage capability is a must in image processing
applications.
 An image of size 1024 * 1024 pixels, in which the intensity
of each pixel is an 8-bit quantity, requires one megabyte of
storage space if the image is not compressed.
 Digital storage for image processing applications falls into
three principal categories:
 Short-term storage for use during processing,
 On-line storage for relatively fast recall, and
 Archival storage, characterized by infrequent access.
 Storage is measured in:
 bytes,
 Kbytes,
 Mbytes,
 Gbytes, and
50

 Image displays in use today are mainly color
(preferably flat screen) TV monitors.
 Monitors are driven by the outputs of image and
graphics display cards that are an integral part of the
computer system.
 In some cases, it is necessary to have stereo displays,
and these are implemented in the form of headgear
containing two small displays embedded in goggles
worn by the user.
51

 Hardcopy devices for recording images include laser
printers, film cameras, heat-sensitive devices, inkjet
units, and digital units, such as optical and CDROM
disks.
 Networking is almost a default function in any
computer system in use today.
In dedicated networks, this typically is not a
problem, but communications with remote sites via the
Internet are not always as efficient.
52

Image Representation
54
x
y
Origin
(0,0)
Pixel

 A digital image is
composed of M rows
and N columns of
pixels each storing a
value
 Pixel values are most
often grey levels in the
range 0-255(black-
white)
 We will see later on
that images can easily
be represented as
matrices.
Image Representation
55

 Images are typically
generated by
illuminating a scene
and absorbing the
energy reflected by
the objects in that
scene
Image Acquisition
57

 Incoming energy lands on a
sensor material responsive
to that type of energy and
this generates a voltage
 Collections of sensors are
arranged to capture images
Image Sensing
Imaging Sensor
Line of Image Sensors
Array of Image Sensors58

 A digital sensor can only measure a limited number
of samples at a discrete set of energy levels
 Quantisation is the process of converting a
continuous analogue signal into a digital
representation of this signal
Image Sampling And Quantization
59

 Remember that a digital image is always only an
approximation of a real world scene.
Image Sampling And Quantization
60

 The spatial resolution of an image is determined by
how sampling was carried out
 Spatial resolution simply refers to the smallest
discernable detail in an image
 Vision specialists will often talk about pixel size
 Graphic designers will talk about dots per inch (DPI)
Spatial Resolution
61

Spatial Resolution
Vision specialists will often talk about pixel
size
62

Spatial Resolution
1024 * 1024 512 * 512 256 * 256
128 * 128 64 * 64 32 * 32
Graphic designers will talk about dots per inch63

 Intensity level resolution refers to the number of
intensity levels used to represent the image
 The more intensity levels used, the finer the level of
detail discernable in an image
 Intensity level resolution is usually given in terms of the
number of bits used to store each intensity level
Intensity Level Resolution
Number of Bits
Number of
Intensity Levels
Examples
1 2 0, 1
2 4 00, 01, 10, 11
4 16 0000, 0101, 1111
8 256 00110011,
0101010116 65,536 101010101010101
0
64

Intensity Level Resolution
128 grey levels (7 bpp) 64 grey levels (6 bpp) 32 grey levels (5 bpp)
16 grey levels (4 bpp) 8 grey levels (3 bpp) 4 grey levels (2 bpp) 2 grey levels (1
bpp)
256 grey levels (8 bits per pixel)
65

 The big question with resolution is always how much is
enough?
 This all depends on what is in the image and what you
would like to do with it
 Key questions include
 Does the image look aesthetically pleasing?
 Can you see what you need to see within the image?
Resolution: How Much Is Enough?
 The picture on the right is fine for counting the
number of cars, but not for reading the number plate66

Thank You…
(This Presentation is Published Only for Educational Purpose)
67

Image processing fundamentals

More Related Content

What's hot (20)

Similar to Image processing fundamentals (20)

More from Dr. A. B. Shinde (20)

Recently uploaded (20)

Image processing fundamentals