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Digital Image Processing:
Introduction
Brian Mac Namee
Brian.MacNamee@comp.dit.ie

Course Website: http://www.comp.dit.ie/bmacnamee
2
of
36

Introduction

“One picture is worth more than ten
thousand words”
Anonymous
3
of
36

Miscellanea
Lectures:
– Thursdays 12:00 – 13:00
– Fridays 15:00 – 16:00

Labs:
– Wednesdays 09:00 – 11:00

Web Site: www.comp.dit.ie/bmacnamee/
– Previous year’s slides are available here
– Slides etc will also be available on WebCT

E-mail: Brian.MacNamee@dit.ie
4
of
36

References
“Digital Image Processing”, Rafael C.
Gonzalez & Richard E. Woods,
Addison-Wesley, 2002
– Much of the material that follows is taken from
this book

“Machine Vision: Automated Visual
Inspection and Robot Vision”, David
Vernon, Prentice Hall, 1991
– Available online at:
homepages.inf.ed.ac.uk/rbf/BOOKS/VERNON/
5
of
36

Contents
This lecture will cover:
– What is a digital image?
– What is digital image processing?
– History of digital image processing
– State of the art examples of digital image
processing
– Key stages in digital image processing
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

6
of
36

What is a Digital Image?
A digital image is a representation of a twodimensional image as a finite set of digital
values, called picture elements or pixels
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

7
of
36

What is a Digital Image? (cont…)
Pixel values typically represent gray levels,
colours, heights, opacities etc
Remember digitization implies that a digital
image is an approximation of a real scene
1 pixel
8
of
36

What is a Digital Image? (cont…)
Common image formats include:
– 1 sample per point (B&W or Grayscale)
– 3 samples per point (Red, Green, and Blue)
– 4 samples per point (Red, Green, Blue, and “Alpha”,
a.k.a. Opacity)

For most of this course we will focus on grey-scale
images
9
of
36

What is Digital Image Processing?
Digital image processing focuses on two
major tasks
– Improvement of pictorial information for
human interpretation
– Processing of image data for storage,
transmission and representation for
autonomous machine perception

Some argument about where image
processing ends and fields such as image
analysis and computer vision start
10
of
36

What is DIP? (cont…)
The continuum from image processing to
computer vision can be broken up into low, mid- and high-level processes
Low Level Process

Mid Level Process

High Level Process

Input: Image
Output: Image

Input: Image
Output: Attributes

Input: Attributes
Output: Understanding

Examples: Noise
removal, image
sharpening

Examples: Object
recognition,
segmentation

Examples: Scene
understanding,
autonomous navigation

In this course we will
stop here
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

11
of
36

History of Digital Image Processing
Early 1920s: One of the first applications of
digital imaging was in the newspaper industry
– The Bartlane cable picture
transmission service
Early digital image
– Images were transferred by submarine cable
between London and New York
– Pictures were coded for cable transfer and
reconstructed at the receiving end on a
telegraph printer
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

12
of
36

History of DIP (cont…)
Mid to late 1920s: Improvements to the
Bartlane system resulted in higher quality
images
– New reproduction
processes based
on photographic
techniques
– Increased number
of tones in
reproduced images

Improved
digital image

Early 15 tone digital
image
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

13
of
36

History of DIP (cont…)
1960s: Improvements in computing
technology and the onset of the space race
led to a surge of work in digital image
processing
– 1964: Computers used to
improve the quality of
images of the moon taken
by the Ranger 7 probe
– Such techniques were used
in other space missions
including the Apollo landings

A picture of the moon taken
by the Ranger 7 probe
minutes before landing
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

14
of
36

History of DIP (cont…)
1970s: Digital image processing begins to
be used in medical applications
– 1979: Sir Godfrey N.
Hounsfield & Prof. Allan M.
Cormack share the Nobel
Prize in medicine for the
invention of tomography,
the technology behind
Computerised Axial
Tomography (CAT) scans

Typical head slice CAT
image
15
of
36

History of DIP (cont…)
1980s - Today: The use of digital image
processing techniques has exploded and
they are now used for all kinds of tasks in all
kinds of areas
– Image enhancement/restoration
– Artistic effects
– Medical visualisation
– Industrial inspection
– Law enforcement
– Human computer interfaces
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

16
of
36

Examples: Image Enhancement
One of the most common uses of DIP
techniques: improve quality, remove noise
etc
17
of
36

Examples: The Hubble Telescope
Launched in 1990 the Hubble
telescope can take images of
very distant objects
However, an incorrect mirror
made many of Hubble’s
images useless
Image processing
techniques were
used to fix this
18
of
36

Examples: Artistic Effects
Artistic effects are
used to make
images more
visually appealing,
to add special
effects and to make
composite images
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

19
of
36

Examples: Medicine
Take slice from MRI scan of canine
heart, and find boundaries between types of
tissue
– Image with gray levels representing tissue
density
– Use a suitable filter to highlight edges

Original MRI Image of a Dog Heart

Edge Detection Image
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

20
of
36

Examples: GIS
Geographic Information Systems
– Digital image processing techniques are used
extensively to manipulate satellite imagery
– Terrain classification
– Meteorology
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

21
of
36

Examples: GIS (cont…)
Night-Time Lights of
the World data set
– Global inventory of
human settlement
– Not hard to imagine
the kind of analysis
that might be done
using this data
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

22
of
36

Examples: Industrial Inspection
Human operators are
expensive, slow and
unreliable
Make machines do the
job instead
Industrial vision systems
are used in all kinds of
industries
Can we trust them?
23
of
36

Examples: PCB Inspection
Printed Circuit Board (PCB) inspection
– Machine inspection is used to determine that
all components are present and that all solder
joints are acceptable
– Both conventional imaging and x-ray imaging
are used
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

24
of
36

Examples: Law Enforcement
Image processing
techniques are used
extensively by law
enforcers
– Number plate
recognition for speed
cameras/automated
toll systems
– Fingerprint recognition
– Enhancement of
CCTV images
25
of
36

Examples: HCI

Try to make human computer
interfaces more natural
– Face recognition
– Gesture recognition

Does anyone remember the
user interface from “Minority
Report”?
These tasks can be
extremely difficult
26
of
36

Key Stages in Digital Image Processing
Image
Restoration

Morphological
Processing

Image
Enhancement

Segmentation

Image
Acquisition

Object
Recognition

Problem Domain

Representation
& Description

Colour Image
Processing

Image
Compression
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

27
of
36

Key Stages in Digital Image Processing:
Image Aquisition
Image
Restoration

Morphological
Processing

Image
Enhancement

Segmentation

Image
Acquisition

Object
Recognition

Problem Domain

Representation
& Description

Colour Image
Processing

Image
Compression
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

28
of
36

Key Stages in Digital Image Processing:
Image Enhancement
Image
Restoration

Morphological
Processing

Image
Enhancement

Segmentation

Image
Acquisition

Object
Recognition

Problem Domain

Representation
& Description

Colour Image
Processing

Image
Compression
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

29
of
36

Key Stages in Digital Image Processing:
Image Restoration
Image
Restoration

Morphological
Processing

Image
Enhancement

Segmentation

Image
Acquisition

Object
Recognition

Problem Domain

Representation
& Description

Colour Image
Processing

Image
Compression
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

30
of
36

Key Stages in Digital Image Processing:
Morphological Processing
Image
Restoration

Morphological
Processing

Image
Enhancement

Segmentation

Image
Acquisition

Object
Recognition

Problem Domain

Representation
& Description

Colour Image
Processing

Image
Compression
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

31
of
36

Key Stages in Digital Image Processing:
Segmentation
Image
Restoration

Morphological
Processing

Image
Enhancement

Segmentation

Image
Acquisition

Object
Recognition

Problem Domain

Representation
& Description

Colour Image
Processing

Image
Compression
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

32
of
36

Key Stages in Digital Image Processing:
Object Recognition
Image
Restoration

Morphological
Processing

Image
Enhancement

Segmentation

Image
Acquisition

Object
Recognition

Problem Domain

Representation
& Description

Colour Image
Processing

Image
Compression
Images taken from Gonzalez & Woods, Digital Image Processing (2002)

33
of
36

Key Stages in Digital Image Processing:
Representation & Description
Image
Restoration

Morphological
Processing

Image
Enhancement

Segmentation

Image
Acquisition

Object
Recognition

Problem Domain

Representation
& Description

Colour Image
Processing

Image
Compression
34
of
36

Key Stages in Digital Image Processing:
Image Compression
Image
Restoration

Morphological
Processing

Image
Enhancement

Segmentation

Image
Acquisition

Object
Recognition

Problem Domain

Representation
& Description

Colour Image
Processing

Image
Compression
35
of
36

Key Stages in Digital Image Processing:
Colour Image Processing
Image
Restoration

Morphological
Processing

Image
Enhancement

Segmentation

Image
Acquisition

Object
Recognition

Problem Domain

Representation
& Description

Colour Image
Processing

Image
Compression
36
of
36

Summary
We have looked at:
– What is a digital image?
– What is digital image processing?
– History of digital image processing
– State of the art examples of digital image
processing
– Key stages in digital image processing

Next time we will start to see how it all
works…

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Digital image processing

  • 1. Digital Image Processing: Introduction Brian Mac Namee Brian.MacNamee@comp.dit.ie Course Website: http://www.comp.dit.ie/bmacnamee
  • 2. 2 of 36 Introduction “One picture is worth more than ten thousand words” Anonymous
  • 3. 3 of 36 Miscellanea Lectures: – Thursdays 12:00 – 13:00 – Fridays 15:00 – 16:00 Labs: – Wednesdays 09:00 – 11:00 Web Site: www.comp.dit.ie/bmacnamee/ – Previous year’s slides are available here – Slides etc will also be available on WebCT E-mail: Brian.MacNamee@dit.ie
  • 4. 4 of 36 References “Digital Image Processing”, Rafael C. Gonzalez & Richard E. Woods, Addison-Wesley, 2002 – Much of the material that follows is taken from this book “Machine Vision: Automated Visual Inspection and Robot Vision”, David Vernon, Prentice Hall, 1991 – Available online at: homepages.inf.ed.ac.uk/rbf/BOOKS/VERNON/
  • 5. 5 of 36 Contents This lecture will cover: – What is a digital image? – What is digital image processing? – History of digital image processing – State of the art examples of digital image processing – Key stages in digital image processing
  • 6. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 6 of 36 What is a Digital Image? A digital image is a representation of a twodimensional image as a finite set of digital values, called picture elements or pixels
  • 7. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 7 of 36 What is a Digital Image? (cont…) Pixel values typically represent gray levels, colours, heights, opacities etc Remember digitization implies that a digital image is an approximation of a real scene 1 pixel
  • 8. 8 of 36 What is a Digital Image? (cont…) Common image formats include: – 1 sample per point (B&W or Grayscale) – 3 samples per point (Red, Green, and Blue) – 4 samples per point (Red, Green, Blue, and “Alpha”, a.k.a. Opacity) For most of this course we will focus on grey-scale images
  • 9. 9 of 36 What is Digital Image Processing? Digital image processing focuses on two major tasks – Improvement of pictorial information for human interpretation – Processing of image data for storage, transmission and representation for autonomous machine perception Some argument about where image processing ends and fields such as image analysis and computer vision start
  • 10. 10 of 36 What is DIP? (cont…) The continuum from image processing to computer vision can be broken up into low, mid- and high-level processes Low Level Process Mid Level Process High Level Process Input: Image Output: Image Input: Image Output: Attributes Input: Attributes Output: Understanding Examples: Noise removal, image sharpening Examples: Object recognition, segmentation Examples: Scene understanding, autonomous navigation In this course we will stop here
  • 11. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 11 of 36 History of Digital Image Processing Early 1920s: One of the first applications of digital imaging was in the newspaper industry – The Bartlane cable picture transmission service Early digital image – Images were transferred by submarine cable between London and New York – Pictures were coded for cable transfer and reconstructed at the receiving end on a telegraph printer
  • 12. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 12 of 36 History of DIP (cont…) Mid to late 1920s: Improvements to the Bartlane system resulted in higher quality images – New reproduction processes based on photographic techniques – Increased number of tones in reproduced images Improved digital image Early 15 tone digital image
  • 13. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 13 of 36 History of DIP (cont…) 1960s: Improvements in computing technology and the onset of the space race led to a surge of work in digital image processing – 1964: Computers used to improve the quality of images of the moon taken by the Ranger 7 probe – Such techniques were used in other space missions including the Apollo landings A picture of the moon taken by the Ranger 7 probe minutes before landing
  • 14. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 14 of 36 History of DIP (cont…) 1970s: Digital image processing begins to be used in medical applications – 1979: Sir Godfrey N. Hounsfield & Prof. Allan M. Cormack share the Nobel Prize in medicine for the invention of tomography, the technology behind Computerised Axial Tomography (CAT) scans Typical head slice CAT image
  • 15. 15 of 36 History of DIP (cont…) 1980s - Today: The use of digital image processing techniques has exploded and they are now used for all kinds of tasks in all kinds of areas – Image enhancement/restoration – Artistic effects – Medical visualisation – Industrial inspection – Law enforcement – Human computer interfaces
  • 16. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 16 of 36 Examples: Image Enhancement One of the most common uses of DIP techniques: improve quality, remove noise etc
  • 17. 17 of 36 Examples: The Hubble Telescope Launched in 1990 the Hubble telescope can take images of very distant objects However, an incorrect mirror made many of Hubble’s images useless Image processing techniques were used to fix this
  • 18. 18 of 36 Examples: Artistic Effects Artistic effects are used to make images more visually appealing, to add special effects and to make composite images
  • 19. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 19 of 36 Examples: Medicine Take slice from MRI scan of canine heart, and find boundaries between types of tissue – Image with gray levels representing tissue density – Use a suitable filter to highlight edges Original MRI Image of a Dog Heart Edge Detection Image
  • 20. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 20 of 36 Examples: GIS Geographic Information Systems – Digital image processing techniques are used extensively to manipulate satellite imagery – Terrain classification – Meteorology
  • 21. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 21 of 36 Examples: GIS (cont…) Night-Time Lights of the World data set – Global inventory of human settlement – Not hard to imagine the kind of analysis that might be done using this data
  • 22. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 22 of 36 Examples: Industrial Inspection Human operators are expensive, slow and unreliable Make machines do the job instead Industrial vision systems are used in all kinds of industries Can we trust them?
  • 23. 23 of 36 Examples: PCB Inspection Printed Circuit Board (PCB) inspection – Machine inspection is used to determine that all components are present and that all solder joints are acceptable – Both conventional imaging and x-ray imaging are used
  • 24. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 24 of 36 Examples: Law Enforcement Image processing techniques are used extensively by law enforcers – Number plate recognition for speed cameras/automated toll systems – Fingerprint recognition – Enhancement of CCTV images
  • 25. 25 of 36 Examples: HCI Try to make human computer interfaces more natural – Face recognition – Gesture recognition Does anyone remember the user interface from “Minority Report”? These tasks can be extremely difficult
  • 26. 26 of 36 Key Stages in Digital Image Processing Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Colour Image Processing Image Compression
  • 27. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 27 of 36 Key Stages in Digital Image Processing: Image Aquisition Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Colour Image Processing Image Compression
  • 28. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 28 of 36 Key Stages in Digital Image Processing: Image Enhancement Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Colour Image Processing Image Compression
  • 29. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 29 of 36 Key Stages in Digital Image Processing: Image Restoration Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Colour Image Processing Image Compression
  • 30. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 30 of 36 Key Stages in Digital Image Processing: Morphological Processing Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Colour Image Processing Image Compression
  • 31. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 31 of 36 Key Stages in Digital Image Processing: Segmentation Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Colour Image Processing Image Compression
  • 32. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 32 of 36 Key Stages in Digital Image Processing: Object Recognition Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Colour Image Processing Image Compression
  • 33. Images taken from Gonzalez & Woods, Digital Image Processing (2002) 33 of 36 Key Stages in Digital Image Processing: Representation & Description Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Colour Image Processing Image Compression
  • 34. 34 of 36 Key Stages in Digital Image Processing: Image Compression Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Colour Image Processing Image Compression
  • 35. 35 of 36 Key Stages in Digital Image Processing: Colour Image Processing Image Restoration Morphological Processing Image Enhancement Segmentation Image Acquisition Object Recognition Problem Domain Representation & Description Colour Image Processing Image Compression
  • 36. 36 of 36 Summary We have looked at: – What is a digital image? – What is digital image processing? – History of digital image processing – State of the art examples of digital image processing – Key stages in digital image processing Next time we will start to see how it all works…