PMB / Westville Campus
MODULE COURSE INFORMATION SHEET - 2024
MODULE CODE: COMP702
MODULE NAME: IMAGE PROCESSING AND COMPUTER VISION
LECTURERS
Module Coordinator – S. VIRIRI
Lecturer - S. VIRIRI
Administrator – Charmaine/Bev
LECTURE
MONDAY
OFFICE
319
319
W / PMB
TELEPHONE
3021/7724
3021/7724
3018 / 5609
TIMETABLE
TIME
VENUE
10:00 – 12:00
305/F47
Online
TUTORIAL
E-MAIL
viriris@ukzn.ac.za
viriris@ukzn.ac.za
magwazac2, bonhomme
TIME
VENUE
TUESDAY
WEDNESDAY
THURSDAY
FRIDAY
MODULE WEBSITE
https://learn2024.ukzn.ac.za/course/view.php?id=5693
CONTENT AND DELIVERY
TUTORIALS
N/A
PRACTICALS
CALCULATORS
N/A
Gonzales R.C. and Woods P., Digital Image Processing, AddisonWesley, 3rd Edition.
N/A
ANNOUNCEMENTS
https://learn2024.ukzn.ac.za/course/view.php?id=5693
DP (DULY PERFORMED)
N/A
ASSESSMENTS
Test1 (20%) + Test2 (30%) + Assignment (20%) + Project (30%)
BAR CODES
Yes
Test 1 (28 March, 2024, 10:00 am)
Test 2 (23 May, 2024, 10:00 am)
PRESCRIBED TEXT
TESTS
MAKE UP TESTS
HOT SEAT
CONSULTATION TIMES
By appointment
Module Objectives:
It covers the theories, techniques and applications of image processing and computer vision in
real-world contexts like biomedical imaging, biometrics, remote sensing, industrial vision,
surveillance and security.
Module Topics:
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Introduction: Image, Graphics, vision and computer; Signal processing overview, Image
processing basics, digital image formats, image processing and vision systems, applications.
Data Structures for Image Processing: Matrices, chains, topological data structures,
relational structures, and hierarchical data structures.
Preprocessing and Image Amelioration: Histogram, histogram transformations,
Modification of the histogram pattern, filtering.
Introduction to Mathematical Morphology: Elements of Set Theory and Logic, Thinning,
erosion, dilation, opening, closing.
Segmentation: Detection of connected components, Thresholding, Edge detection, region
detection
Features Extraction and Representation: region identification, description and
representation of contours, description and representation of regions.
Linear Image Transformations: Basic Theory, Hadammard Transform, Haar Transform,
Fourier Transform, Discrete Cosine Transform, Wavelets.
Image Data Compression: Presentation of different techniques and different norms of
compression, Coding, Fractal Image Compression.
Elements of Pattern Recognition: Different methods of pattern recognition, Learning and
Clustering, structural pattern recognition.
Texture Analysis: Statistical texture description, Syntactic texture description methods,
applications.
Motion Analysis: Optical flow, moving Object detection and Tracking, Behavior Detection
and Modeling, Kalman filtering.
Tests and Assignments:
There will be two tests, two assignments and a project.
NB: A doctors' certificate is required if you miss a test.
Tests
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and Assignments Dates:
Test 1: 28 March, 2024
Test 2: 23 May, 2024
Assignment: (See assignment outline)
Project: (See project outline)
FINAL MARK = 0.3*Test1 + 0.3*Test2 + 0.2*Assignment + 0.2*Project
References: (Useful Textbooks)
1. Gonzales R.C. and Woods P., Digital Image Processing, Addison-Wesley, 3rd Edition.
2. Sonka M. Hlavac V. and Doyle R., Image Processing, Analysis, and Machine Vision, PWS
Publishing.
3. Burger W. and Burge M.J., Digital Image Processing, Springer.
4. Duda R. O., Hart P. E. and Stork D. G., Pattern Classification, Wiley Interscience.
5. Snyder W.E. and Qi H., Machine Vision, Cambridge.