Subject Descriptions - Subject Information

Calendar: 2017 Undergraduate
Faculty: Faculty of Engineering and Information Sciences
Department: School of Computing and Information Technology

Subject Information
Subject Code CSCI435
Subject Name Computer Vision Algorithms and Systems
Credit Points 6
Pre-Requisites 24cp @CSCI 300 level
Co-Requisites None.
Restrictions None.
Equivalence None.
Assessment Three assignments (60%), final examination (40%)
General Subject Yes.
EFTSL (Non Weighted) 0.125
Non Weighted Student Contribution Amounts
Commonwealth Supported (HECS) Students Only
Pre-1997 Pre-2005 Post-2005 Post-2008 Post-2009 Post-2010
$ 1131  $ 1131  $ 1131  $ 1131  $ 1131  $ 1131 
Weighted Student Contribution Amounts
Commonwealth Supported (HECS) Students Only
1771-Bachelor of Laws (Honours) (Direct Entry)
1777-Bachelor of Laws (Direct Entry)
1827-Bachelor of International Studies - Bachelor of Laws
1845-Bachelor of Information Technology - Bachelor of Laws
1852-Bachelor of Business Information Systems - Bachelor of Laws
351-Bachelor of Laws (Honours)
760-Bachelor of Communication and Media Studies - Bachelor of Laws
770-Bachelor of Laws (Graduate Entry)
771-Bachelor of Arts - Bachelor of Laws
771H-Bachelor of Arts - Bachelor of Laws
772-Bachelor of Creative Arts - Bachelor of Laws
773-Bachelor of Commerce - Bachelor of Laws
774-Bachelor of Mathematics - Bachelor of Laws
775-Bachelor of Science - Bachelor of Laws
775H-Bachelor of Science - Bachelor of Laws
775M-Course information not Found
779-Bachelor of Engineering - Bachelor of Laws
858-Bachelor of Journalism - Bachelor of Laws
Work Experience No
Tutorial Enrolment Information No tutorials for this subject

Subject Availability
Session Spring  (24-07-2017 to 16-11-2017)
Campus Wollongong
Delivery Method On Campus
Instance Name Class 1
Course Restrictions No restrictions
Contact Hours Two Hour Lecture
Lecturer(s) and
Cons. times
Wanqing Li
Coordinator(s) and
Cons. times
Wanqing Li
Instance Comment  
Census Date 31-08-2017

Subject Description
This subject is designed to equip the student with an understanding of the fundamental tools required to analyse, design and implement computer vision systems. Topics covered include low-level, mid-level, and high-level vision; image formation; camera model and calibration, stereo vision; edge detection and segmentation; thinning and skeletonising, binary morphological operations; object recognition, image interpretation and scene understanding.

Subject Learning Outcomes
On successful completion of this subject, students will be able to:
1. Understand the principle of digital image and video cameras.
2. Use image enhancement techniques.
3. Use object detection and recognition techniques.
4. Use video processing techniques to detect moving objects.
5. Design and implement basic computer vision systems for real applications.

Extra Information
Generic Extra Information:
Assumed Knowledge: 1st year University Calculus, Algebra and Probability

Textbook Information

Text book information is available via the UniShop website:

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