Digital Image Processing
Lecture 1: Introduction
Prof. Charlene Tsai
tsaic@cs.ccu.edu.tw
http://www.cs.ccu.edu.tw/~tsaic/teaching/spring2007_dip/main.html
Why digital image processing?
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Image is better than any other information
form for human being to perceive.
Humans are primarily visual creatures –
above 90% of the information about the world
(a picture is better than a thousand words)
However, vision is not intuitive for machines
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projection of 3D world to 2D images => loss of
information
interpretation of dynamic scenes, such as a
moving camera and moving objects
What is digital image processing?
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Image understanding, image analysis, and
computer vision aim to imitate the process of
human vision electronically
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Image acquisition
Preprocessing
Segmentation
Representation and description
Recognition and interpretation
General procedures
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Goal: to obtain similar effect provided by
biological systems
Two-level approaches
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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
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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
3x3 neighborhood
Origin (Ox,Oy)
Pixel Value
Pixel Region
Spacing (Sy)
Spacing (Sx)
Low level image processing
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Image compression
Noise reduction
Edge extraction
Contrast enhancement
Segmentation
Thresholding
Morphology
Image restoration
Low level image processing
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Image compression
Noise reduction
Edge extraction
Contrast enhancement
Segmentation
Thresholding
Morphology
Image restoration
Low level image processing
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Image compression
Noise reduction
Edge extraction
Contrast enhancement
Segmentation
Thresholding
Morphology
Image restoration
Low level image processing
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Image compression
Noise reduction
Edge extraction
Contrast enhancement
Segmentation
Thresholding
Morphology
Image restoration
Low level image processing
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Image compression
Noise reduction
Edge extraction
Contrast enhancement
Segmentation
Thresholding
Morphology
Image restoration
Low level image processing
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Image compression
Noise reduction
Edge extraction
Contrast enhancement
Segmentation
Thresholding
Morphology
Image restoration
Low level image processing
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Image compression
Noise reduction
Edge extraction
Contrast enhancement
Segmentation
Thresholding
Morphology
Image restoration
Dilation
Erosion
Low level image processing
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Image compression
Noise reduction
Edge extraction
Contrast enhancement
Segmentation
Thresholding
Morphology
Image restoration
High level image understanding
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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 highlevel goal.
High level image understanding
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What are the high-level components?
What tasks can be achieved?
Traces
(vessel centerlines)
Landmarks
(bifurcation/cross
over)
Applications
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Medicine
Defense
Meteorology
Environmental science
Manufacture
Surveillance
Crime investigation
Applications: Medicine
CT
PET
(computed
Tomography)
(Positron Emission
Tomography
PET/CT
Applications: Meteorology
Applications: Environmental Science
Applications: Manufacture
Application: Surveillance
Car Tracking Project
from CMU: Tracking
cars in the surrounding
road scene and then
generating a "bird's
eye view" of the road.
Courtesy of Simon Baker: http://www.ri.cmu.edu/projects/project_526.html
Applications: Crime Investigation
Fingerprint enhancement
What are the difficulties?
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Poor understanding of the human vision
system
Do you see a young or an old lady?
What are the difficulties?
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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?
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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
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What we read
What we hear
What we see
What we hear + see
What we say ourselves
What we do ourselves
10%
20%
30%
50%
70%
90%
Class Format – Efficiency of Learning
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This leads to in-class discussion and quizzes.
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50-minute lecture
Remaining for group discussion & in-class
quiz
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Course requirements
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In-class quizzes
4 Homework assignments
Final project
Midterm exam
Final exam
Peer learning is encouraged
BUT, NO PLAGIARISM!!!
(20% deduction if caught)
10%
25%
25%
20%
20%
Textbooks
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Problems in picking a good textbook:
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Prescribed:
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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
tend to be too expensive
Rafael C. Gonzalez, Richard E. Woods: Digital Image
Processing. Prentice Hall; 2nd edition, 2002
Other references (used in 2005):
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Alasdair McAndrew: Introduction to Digital Image
Processing with Matlab, 2004.
Programming Tools
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Matlab with Image Processing Toolbox for
homework exercises
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MATLAB Tutorial:
http://www.mathworks.com/products/matlab/matlab_tutorial.html
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MATLAB documentation:
http://www.mathworks.com/access/helpdesk/help/techdoc/matlab
.shtml
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User-contributed MATLAB IP functions:
http://www.mathworks.com/matlabcentral/fileexchange/loadCateg
ory.do?objectType=category&objectId=26
More on Matlab
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University of Colorado Matlab Tutorials:
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A decent collection of Matlab tutorials, including
one focusing on image processing
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http://amath.colorado.edu/computing/Matlab/tutorials.html
http://amath.colorado.edu/courses/4720/2000Spr/Labs/Workshee
ts/Matlab_tutorial/matlabimpr.html
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Term project
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Group project of 2~3 people
I decide the format of the term project
You decide your own topic that interests you
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So, starting thinking about it!!!
You may implement your project with any
programming language of your preference.
In-class quiz
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Goal: to enhance learning
Open-book/open-notes format
Group effort of 2~3 people to encourage
discussion and peer learning
Looking ahead: lecture2
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Image types
File format
Matlab programming.