FIT3081 Image processing
Faculty of Information Technology
FIT3081 Image processing is a level 3, 6-credit-point, undergraduate unit from the Faculty of Information Technology, offered in 2022 in Semester 1 at Malaysia. It has no prerequisites.
- Credit points
- 6
- Offered in 2022
- Semester 1
- Malaysia
- Assessment
- Exam 50%
- and 3 other tasks
- Workload
- 144 hours
- per semester
This is the 2022 handbook entry. See the 2023 entry.
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Requisites
Before FIT3081
No prerequisites or corequisites besides the enrolment rules below.
After FIT3081
No unit lists FIT3081 as a prerequisite in the 2022 handbook.
Enrolment rules
Prerequisite: FIT2004 (or CSE2304)
Prohibition: CSE3314
Overview
This unit introduces fundamental image processing techniques for the digital manipulation of 2D image data. Algorithms explored include those for edge detection, image enhancement, feature and shape extraction, segmentation and noise removal. The unit provides students an opportunity to develop theoretical understanding of these algorithms, and practical skills in implementing and applying them to real image data.
Offerings in 2022
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Malaysia | On campus |
Assessment
- Assignment 1AssignmentThreshold hurdle10%
- Assignment 2AssignmentThreshold hurdle25%
- Class ParticipationParticipationThreshold hurdle15%
- Image Processing - PAPER 1ExamThreshold hurdle50%
Learning outcomes
When you finish this unit, you should be able to:
- 1
Explain the processes of image formation, acquisition, processing and analysis;
- 2
Explain the type of algorithm required for a particular image processing task among a wide range of available methodologies;
- 3
Develop programs for manipulating grey level and colour images using standard image processing algorithms;
- 4
Develop and analyse software for image segmentation, image classification, image data mining, and computer vision;
- 5
Develop algorithms to extract and analyse features in medical, document, and other images;
- 6
Participate in a team as an image processing specialist communicating with other team members to develop image processing software.
Workload and teaching
- Workshops48 hours
- Teaching approachActive learning
- Teaching approachProblem-based learning
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning and online engagement.
Learning resources
Required resources
Prescribed text(s)
Limited copies of prescribed texts are available for you to borrow in the library.
- R. C. Gonzalez and R. E. Woods, Digital Image Processing, Pearson; 4th edition, 2017
- R. C. Gonzalez and R. E. Woods, Digital Image Processing Using Matlab, 2nd Edition, 2009
Technology resources
Required software
MATLAB
Where it fits
FIT3081 is part of 3 areas of study in the 2022 handbook.
Contacts
- Chief Examiners
- Associate Professor Anuja Dharmaratne
Common questions
What are the prerequisites for FIT3081?
FIT3081 has no prerequisites, but enrolment rules apply.
When is FIT3081 offered?
In 2022, FIT3081 runs in Semester 1 at Malaysia.
How much work is FIT3081?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does FIT3081 have an exam?
Yes. The exam is worth 50% of the final mark, alongside 3 other tasks.
Which majors and minors include FIT3081?
FIT3081 is part of Advanced computer science, Computational science and Software engineering.