imageprocessing introduction
TRANSCRIPT
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Digital Image Processing:
Introduction
Er. Suman Thapar
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36Introduction
One picture is worth more than ten
thousand words
Anonymous
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36References
Digital Image Processing, Rafael C.Gonzalez & Richard E. Woods,
Addison-Wesley, 2002
Much of the material that follows is taken fromthis book
Machine Vision: Automated Visual
Inspection and Robot Vision, DavidVernon, Prentice Hall, 1991
Available online at:
homepages.inf.ed.ac.uk/rbf/BOOKS/VERNON/
http://homepages.inf.ed.ac.uk/rbf/BOOKS/VERNON/http://homepages.inf.ed.ac.uk/rbf/BOOKS/VERNON/toc.htmhttp://homepages.inf.ed.ac.uk/rbf/BOOKS/VERNON/ -
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36Contents
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
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36What is a Digital Image?
A digital imageis a representation of a two-dimensional image as a finite set of digital
values, called picture elements or pixels
ImagestakenfromGonzalez&Woods,
DigitalIma
geProcessing(2002)
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36What is a Digital Image? (cont)
Pixel values typically represent gray levels,colours, heights, opacities etc
Rememberdigitizationimplies that a digital
image is an approximationof a real scene
1 pixel
ImagestakenfromGonzalez&Woods,
DigitalIma
geProcessing(2002)
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36What 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
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36What is Digital Image Processing?
Digital image processing focuses on twomajor 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
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36What is DIP? (cont)
The continuum from image processing tocomputer vision can be broken up into low-,
mid- and high-level processes
Low Level Process
Input:Image
Output:Image
Examples:Noise
removal, imagesharpening
Mid Level Process
Input:Image
Output:Attributes
Examples:Object
recognition,segmentation
High Level Process
Input:Attributes
Output:Understanding
Examples: Scene
understanding,autonomous navigation
In this course we will
stop here
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36History of DIP (cont)
1960s:Improvements in computingtechnology 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 7probe
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 landingImagestakenfromGonzalez&Woods,
DigitalIma
geProcessing(2002)
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36History of DIP (cont)
1970s:Digital image processing begins tobe 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 behindComputerised Axial
Tomography (CAT) scansTypical head slice CAT
image
ImagestakenfromGonzalez&Woods,
DigitalIma
geProcessing(2002)
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36History of DIP (cont)
1980s - Today:The use of digital imageprocessing 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
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36Examples: Image Enhancement
One of the most common uses of DIPtechniques: improve quality, remove noise
etc
Im
agestakenfromGonzalez&Woods,
DigitalIma
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36Examples: The Hubble Telescope
Launched in 1990 the Hubbletelescope can take images of
very distant objects
However, an incorrect mirrormade many of Hubbles
images useless
Image processingtechniques were
used to fix this
http://en.wikipedia.org/wiki/Image:Hst_sts82.jpg -
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36Examples: Artistic Effects
Artistic effects areused to make
images more
visually appealing,to add special
effects and to make
composite images
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36Examples: 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 ImageImagestakenfromGonzalez&Woods,
DigitalIma
geProcessing(2002)
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36Examples: GIS
Geographic Information Systems Digital image processing techniques are used
extensively to manipulate satellite imagery
Terrain classification Meteorology
Im
agestakenfromGonzalez&Woods,
DigitalIma
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36Examples: GIS (cont)
Night-Time Lights ofthe Worlddata set
Global inventory of
human settlement Not hard to imagine
the kind of analysis
that might be done
using this data
Im
agestakenfromGonzalez&Woods,
DigitalIma
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36Examples: Industrial Inspection
Human operators areexpensive, slow and
unreliable
Make machines do thejob instead
Industrial vision systems
are used in all kinds ofindustries
Can we trust them?
Im
agestakenfromGonzalez&Woods,
DigitalIma
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36Examples: 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
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36Examples: Law Enforcement
Image processingtechniques are used
extensively by law
enforcers Number plate
recognition for speed
cameras/automated
toll systems
Fingerprint recognition
Enhancement of
CCTV imagesImagestakenfromGonzalez&Woods,
DigitalIma
geProcessing(2002)
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36Examples: HCI
Try to make human computerinterfaces more natural
Face recognition
Gesture recognitionDoes anyone remember the
user interface from Minority
Report?These tasks can be
extremely difficult
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36Key Stages in Digital Image Processing
Image
Acquisition
Image
Restoration
Morphological
Processing
Segmentation
Representation
& Description
ImageEnhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
Compression
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Key Stages in Digital Image Processing:
Image Aquisition
Image
Acquisition
Image
Restoration
Morphological
Processing
Segmentation
Representation
& Description
ImageEnhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
CompressionImagestakenfromGonza
lez&Woods,
DigitalImageProcessing(2002)
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Key Stages in Digital Image Processing:
Image Enhancement
Image
Acquisition
Image
Restoration
Morphological
Processing
Segmentation
Representation
& Description
ImageEnhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
CompressionImagestakenfromGonza
lez&Woods,
DigitalImageProcessing(2002)
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Key Stages in Digital Image Processing:
Image Restoration
Image
Acquisition
Image
Restoration
Morphological
Processing
Segmentation
Representation
& Description
ImageEnhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
CompressionImagestakenfromGonza
lez&Woods,
DigitalImageProcessing(2002)
K St i Di it l I P i
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Key Stages in Digital Image Processing:
Morphological Processing
Image
Acquisition
Image
Restoration
Morphological
Processing
Segmentation
Representation
& Description
ImageEnhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
CompressionImagestakenfromGonza
lez&Woods,
DigitalImageProcessing(2002)
K St i Di it l I P i
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Key Stages in Digital Image Processing:
Segmentation
Image
Acquisition
Image
Restoration
Morphological
Processing
Segmentation
Representation
& Description
ImageEnhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
CompressionImagestakenfromGonza
lez&Woods,
DigitalImageProcessing(2002)
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Key Stages in Digital Image Processing:
Object Recognition
Image
Acquisition
Image
Restoration
Morphological
Processing
Segmentation
Representation
& Description
ImageEnhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
CompressionImagestakenfromGonza
lez&Woods,
DigitalImageProcessing(2002)
K St i Di it l I P i
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Key Stages in Digital Image Processing:
Representation & Description
Image
Acquisition
Image
Restoration
Morphological
Processing
Segmentation
Representation
& Description
ImageEnhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
CompressionIm
agestakenfromGonza
lez&Woods,
DigitalImageProcessing(2002)
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Key Stages in Digital Image Processing:
Colour Image Processing
Image
Acquisition
Image
Restoration
Morphological
Processing
Segmentation
Representation
& Description
ImageEnhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
Compression
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36Summary
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