Digital Image Processing Lecture 1: IntroductionProf. Charlene Tsai

tsaic@cs.ccu.edu.tw

http://www.cs.ccu.edu.tw/~tsaic/teaching/spring2007_dip/main.html

Why digital image processing? Image is better than any other information for

m for human being to perceive. Humans are primarily visual creatures – abov

e 90% of the information about the world (a picture is better than a thousand words)

However, vision is not intuitive for machines projection of 3D world to 2D images => loss of inf

ormation interpretation of dynamic scenes, such as a movin

g camera and moving objects

What is digital image processing? Image understanding, image analysis, and co

mputer vision aim to imitate the process of human vision electronically Image acquisition Preprocessing Segmentation Representation and description Recognition and interpretation

General procedures

Goal: to obtain similar effect provided by biological systems

Two-level approaches Low level image processing. Very little knowledge

about the content or semantics of images High level image understanding. Imitating human

cognition and ability to infer information contained in the image.

Low level image processing

Very little knowledge about the content of the images.

Data are the original images, represented as matrices of intensity values, i.e. sampling of a continuous field using a discrete grid.

Focus of this course.

Low level image processing

Origin (Ox,Oy)

Spacing (Sy)

Spacing (Sx)

Pixel Value

Pixel Region

3x3 neighborhood

Low level image processing

Image compression Noise reduction Edge extraction Contrast enhancement Segmentation Thresholding Morphology Image restoration

Low level image processing

Image compression Noise reduction Edge extraction Contrast enhancement Segmentation Thresholding Morphology Image restoration

Low level image processing

Image compression Noise reduction Edge extraction Contrast enhancement Segmentation Thresholding Morphology Image restoration

Low level image processing

Image compression Noise reduction Edge extraction Contrast enhancement Segmentation Thresholding Morphology Image restoration

Low level image processing

Image compression Noise reduction Edge extraction Contrast enhancement Segmentation Thresholding Morphology Image restoration

Low level image processing

Image compression Noise reduction Edge extraction Contrast enhancement Segmentation Thresholding Morphology Image restoration

Low level image processing

Image compression Noise reduction Edge extraction Contrast enhancement Segmentation Thresholding Morphology Image restoration ErosionDilation

Low level image processing

Image compression Noise reduction Edge extraction Contrast enhancement Segmentation Thresholding Morphology Image restoration

High level image understanding To imitate human cognition according to the

information contained in the image. Data represent knowledge about the image

content, and are often in symbolic form. Data representation is specific to the high-

level goal.

High level image understanding What are the high-level components? What tasks can be achieved?

Landmarks(bifurcation/crossover)

Traces(vessel centerlines)

Applications

Medicine Defense Meteorology Environmental science Manufacture Surveillance Crime investigation

Applications: Medicine

CT

(computed Tomography)

PET

(Positron Emission Tomography

PET/CT

Applications: Meteorology

Applications: Environmental Science

Applications: Manufacture

Application: Surveillance

Courtesy of Simon Baker: http://www.ri.cmu.edu/projects/project_526.html

Car Tracking Project from CMU: Tracking cars in the surrounding road scene and then generating a "bird's eye view" of the road.

Applications: Crime Investigation

Fingerprint enhancement

What are the difficulties? Poor understanding of the human vision

system

Do you see a young or an old lady?

What are the difficulties?

Human vision system tends to group related regions together, not odd mixture of the two alternatives.

Attending to different regions or contours initiate a change of perception

This illustrates once more that vision is an active process that attempts to make sense of incoming information.

What are the difficulties?

The interpretation is based heavily on prior knowledge.

Just some fun visual perception games

Can you count the dots?

More …

Do you see squares?

More at http://scientificpsychic.com/graphics/index.html

Example: Detection of ozone layer hole

Over the Antarctic, normal value around 300 DU

Class Format – Efficiency of Learning What we read 10% What we hear 20% What we see 30% What we hear + see 50% What we say ourselves 70% What we do ourselves 90%

Class Format – Efficiency of Learning This leads to in-class discussion and quizzes.

50-minute lecture Remaining for group discussion & in-class

quiz

Course requirements

In-class quizzes 10% 4 Homework assignments 25% Final project 25% Midterm exam 20% Final exam 20%

Peer learning is encouraged BUT, NO PLAGIARISM!!!

(20% deduction if caught)

Textbooks

Problems in picking a good textbook: Hard to find a textbook of the right level --- too easy or too

hard. Hard to find a textbook of the right price --- good books ten

d to be too expensive Prescribed:

Rafael C. Gonzalez, Richard E. Woods: Digital Image Processing. Prentice Hall; 2nd edition, 2002

Other references (used in 2005): Alasdair McAndrew: Introduction to Digital Image Processin

g with Matlab, 2004.

Programming Tools

Matlab with Image Processing Toolbox for homework exercises MATLAB Tutorial: http://www.mathworks.com/products/matl

ab/matlab_tutorial.html

MATLAB documentation:http://www.mathworks.com/access/helpdesk/help/techdoc/matlab.shtml

User-contributed MATLAB IP functions: http://www.mathworks.com/matlabcentral/fileexchange/loadCategory.do?objectType=category&objectId=26

More on Matlab

University of Colorado Matlab Tutorials: A decent collection of Matlab tutorials, including o

ne focusing on image processing http://amath.colorado.edu/computing/Matlab/tutorials.html http://amath.colorado.edu/courses/4720/2000Spr/Labs/Workshee

ts/Matlab_tutorial/matlabimpr.html

Term project

Group project of 2~3 people I decide the format of the term project You decide your own topic that interests you

So, starting thinking about it!!! You may implement your project with any

programming language of your preference.

In-class quiz

Goal: to enhance learning Open-book/open-notes format Group effort of 2~3 people to encourage

discussion and peer learning

Looking ahead: lecture2

Image types File format Matlab programming.