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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

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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,

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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

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agestakenfromGonzalez&Woods,

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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,

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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,

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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,

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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

K St i Di it l I P i

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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)

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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)

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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)

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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