Introduction to Image Processing

Grass

Sky

TreeTree

? ?

Introduction

A picture is worth more than a thousand words

Aims and Objectives

• A general introduction to the common techniques of image processing and its relations with Computer Vision and Computer Graphics

• To review and understand the principal approaches used, which provide as the basis for further study of the related fields

• To offer practical experience in writing programs that manipulate images, using examples in Java

Module Information

• Prerequisites: G51MCS, G51PRG or equivalent

• Course Structure– Lecture: 2 hours/week– Practical: 1 hour/week (starting

week 3/4)

• Assessment– Programming Assignment (40%)– 1-hour exam (60%)

• Handoutshttp://moodle.nottingham.ac.uk OR

http://jupiter.nottingham.edu.my/~kczshh/G52IIP/

• Reference Books

– Digital Image Processing, 3rd Edition by Rafael Gonzalez & Richard Woods

– Digital Image Processing

Using Java by Nick Efford

Image Processing, Vision, Graphics

• In image processing we do things like – removing noise from images– finding edges and features in

images– generally changing 2D images

to other 2D images

• In computer vision we do things like– finding moving objects in a

scene– recognising objects from a

database– build abstract models of the

world from images– generally extract information

about 3D world from 2D images

• In computer graphics we do things like– creating a 3D model,

with realistic shape, colour, texture, and project it to 2D for viewing

– animate the 3D model– creating a virtual world

and animate the objects in it

• The link between imaging and graphics– image based modelling

Computer Graphics

(Courtesy of Michael Cohen)

Image

Output

ModelSyntheticCamera

Real Scene

Computer Vision

Real Cameras

Model

Output

(Courtesy of Michael Cohen)

Vision and Graphics Combined

Model Real Scene

Real Cameras

Image

Output

SyntheticCamera

(Courtesy of Michael Cohen)

Image Processing (1)

Image Enhancement

Image Restoration

Image Processing (2)

Image Compression

Computer Vision: Recognition

Another Useful Paradigm

• Three Processing Levels: Low-level process:

– primitive operations like noise reduction, contrast enhancement, image sharpening…

– input: image output: image Mid-level process:

– tasks like segmentation, representation, description– input: image output: attributes extracted from images

High-level process– “making sense” of an ensemble of recognized objects– input: image (sequence) output: interpretation

DigitalImage Processing

Computer Vision

Proposed Contents

• Fundamentals • Basic Image Manipulation• Noise and Spatial Techniques• Point, Line & Edge Detection • Image Segmentation &

Representation• Basic Spectral Techniques• Others if time permits

Words of Caution• Lecture Contents

slightly mathematical + practical attendance required to understand lecture materials not difficult but leaving it until the last minute can be

disastrous further readings are required if you intend to

undertake DIP related projects

• Reference Texts read them if you need more detailed explanations

than what is found in the lecture slides

• Tips for Passing this Module coursework must be submitted practise by solving the past exam questions show detailed steps of how the final answers are

derived in your answer scripts

Light and Colour

The spectrum of electromagnetic waves:

http://www.nasa.gov

Radio Images

knee spine head

visible infrared radio

• Radio Band− medicine and astronomy

Radar Images

mountains in southeast Tibet

• Microwave Band

Thermal Images

human body dispersesheat (red pixels)

different colours indicatevarying temperatures

• Infrared Band

Remote Sensing

hurricane Andrewtaken by NOAA GEOS

America at night (Nov. 27, 2000)

• Visible and Infrared Bands− weather and environmental observations

Light Microscopy

taxol (250) cholesterol (40) microprocessor (60)

• Visible Band− pharmaceuticals and microinspection

Fluorescence Microscopy

normal corn smut corn

• Ultraviolet Band

X-Ray Imaging

chest head

Gamma-Ray Imaging

positron emission tomography

Cygnus Loop in theconstellation of Cygnus

Other Non-Electromagnetic Imaging Modalities

• Acoustic Imaging translate “sound waves” into image signals

• Electron Microscopy shine a beam of electrons through a

specimen

• Synthetic Images in Computer Graphics computer generated (non-existent in the

real world)

Application Areas• Space

cosmic radiation, images from Hubble space telescope and interplanetary probe

• Medicine multitude of diagnostic medical images

• Remote Sensing and GIS terrain classification and meteorology

• Industrial Inspection replace human operators with machines

• Security and Law Enforcement surveillance and biometrics

• Human Computer Interaction more natural interface using face, gesture recognition

Acknowlegements

Slides are modified based on the original slide set from Dr Li Bai, The University of Nottingham, Jubilee Campus plus adoptions from the following sources:

• Digital Image Processing book by Gonzalez and Woods• robots.stanford.edu/cs223b07/notes/CS223B-L1-Intro.ppt • www.nmc.teiher.gr/activities/MASTERS/intensive/

IP_Chania/prez/TEI/bebis/CV_Overview.ppt• http://www.csee.wvu.edu/~xinl/courses/ee465/intro.ppt