Synopsis - MetaLab - Universiti Tenaga Nasional

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CGMB4
2
4
IMAGE PROCESSING & COMPUTER VISION


Semester 2
, 2007/2008

CGMB4
2
4
IMAGE PROCESSING & COMPUTER VISION



Lecturer:

Mr. Chen Soong Der

Office:

BW
-
3
-
C1
7

Telephone:

6
03

8921

23
83

E
-
mail:

chensoong
@uniten.edu.my

Website

http://m
etalab.uniten.edu.my/~
chensd




Course Overview

Concepts and algorithms of image an
alysis, restoration, enhancement and compression are
discussed during the lectures. The lab component of the course consists of programming
exercise on implementing the image
-
processing algorithms using C programming language.
The assignment component of t
he course requires student to design and implement a computer
program that can solve simple vision problem. The quizzes, test and final examination serve to
evaluate the student’s understanding of various image processing algorithms as well as their
abilit
y to apply the knowledge to solve simple problem related to digital image processing.


Course Objectives:

At the end of the course, students should be able to



Define the objective(s) for each of the image processing algorithm



Perform the image processing
algorithms manually



Build computer program that implement the image processing algorithms using
programming language



Combines various algorithms to solve simple problem related to digital image
processing


Main Textbook
:

1.

Scott E Umbaugh:

Computer Vision a
nd Image Processing, Prentice Hall, USA,

ISBN:0
-
13
-
790882
-
2


References:

1.

Baxes G.A.: Digital Image Processing


Principles and Applications, John Wiley &
Sons, New York, 1994.

2.

Phillips D.: Image Processing in C


Analyzing and Enhancing Digital Images, R&D

Publications, Kansas, 1994.



Assessment

Automated Quizzes

1
0
%

Lab

10
%

Coding
A
ssignment

10
%

Tests (2)

20%

Final Examination

50%

Total:

100%



Meetings



Lecture:

Tue

1000
-
12
00

BW
-
2
-
R06

Lab:

Wed (1A)

1400

16
00

BW
-
4
-
L1
7

Siti Salwa

Fri

080
0
-
0900

BW
-
2
-
R06

Wed (1B)

1100

13
00

BW
-
4
-
L1
7

Siti Salwa


Class Policies

1.

Attendance for lectures

and lab sessions is compulsory. Attendance for less than 80% of
the lectures/labs will result in students being barred from taking the Final Exam.

2.

Dress in pro
per attire

which
correspond
s

to Universiti Tenaga Nasional dress code.

3.

If you are absent from the lecture due to



Sickness


MC is required



Emergency


letter of guardian is required

CGMB4
2
4
IMAGE PROCESSING & COMPUTER VISION


Semester 2
, 2007/2008

Lesson Plan

(Tentative)

Start
Date

Week

Topic

Textbook
(Chapter)

Lab

03
/
12
/200
7

1

Course Outline



No lab

10
/
12
/200
7

2

1.

Computer Vision

2.

Image Processing

3.

Computer Imaging Systems

4.

The CVIPtools Software


1

No lab

17/12
/
200
7

3

5.

Human Visual Perception



The Human Visual System



Spatial Frequency Resolution



Brightness Adaptation



Tem
poral Resolution

6.

Image Representation



Binary images



Gray
-
scale mages



Color mages

7.

Digital Image File Formats

(guided
self study)


1

Lab #1

24/12
/2007

4

1.

Introduction



Overview



System Model

2.

Preprocessing



Region of Interest Image
Geometry



Image Algebra



Spatial

Filters



Image Quantization



2

Lab #2

31/12
/2007

5

3.

Edge/Line Detection



Roberts operator



Sobel & Prewitt operators



Kirsch & Robinson compass
masks

2

Lab #3

07/01/2008

6



Frei
-
Chen masks



Edge operator performance



Hough Transform


2

Lab #3


14/01/2008

7

4.

Se
gmentation



Overview



Region growing & shrinking



Clustering Techniques



Boundaries detection



Morphological Filtering


2

Lab #4


21/01/2008

8

5.

Discrete Transform



How to transform?


2

Lab #4

28/01/2008

9



Why transform?



Filtering



2D transform using 1D vector


2

Lab #5

04/02/2008

10

6.

Feature Extraction & Analysis

2

Lab #5

CGMB4
2
4
IMAGE PROCESSING & COMPUTER VISION


Semester 2
, 2007/2008

Start
Date

Week

Topic

Textbook
(Chapter)

Lab



Feature Vectors



Binary object features



Histogram features



Color, spectral features



Pattern Classification


11/02/2008

11


Semester Break



18/02/2008

12

1.

Introduction



System Model

2.

Noise remova
l using spatial filters



Order filters



Mean filters



Adaptive filters


3

Lab #6

25
/02/2008

13

3.

Frequency domain filters



Inverse filter

4.

Geometry Transform



Spatial transform



Gray
-
level interpolation


3

Lab #6

03/03/2008

14

1.

Gray
-
scale Modification



Histogram mo
dification



Adaptive Contrast Enhancement

2.

I
mage Sharpening



High
-
pass frequency emphasis

3.

I
mage Smoothing



Mean & median filtering



Low pass filter


4





Lab #7

10/03/2008

15

1.

Introduction



Fidelity criteria

2.

Lossless Compression



Probability & Code Length



Huffm
an Coding



Entropy



Run
-
Length Coding

3.

Lossy Compression



JPEG Compression system



5






Lab #7

17/03/2008

1
6




24/03/2008

-

05
/04/2008


17

Final Exam