Unit details

CITS4402 Computer Vision

Credit

6 points

Offering
(see Timetable)

Availability	Location	Mode
Semester 1	UWA (Perth)	Face to face
Semester 1	Online	Online timetabled

Content

Computer vision is the science of automatically computing information and making decisions from an observed image, image set or an image sequence. It combines concepts from 'image processing' (in the spatial and frequency domains) and 'pattern recognition'. Computer vision has a wide number of potential applications, including satellite imaging, control and measurement, industrial inspection, surveillance (e.g. face recognition) and medical applications. This unit covers topics such as binary image analysis, greyscale image manipulation, linear and nonlinear filtering, feature extraction, image enhancement, image segmentation and recognition. It also covers camera calibration and projective geometry and how three-dimensional information can be reconstructed from single images, stereo pairs of images and motion sequences. In the future, it is anticipated that computer vision systems will become prevailing, and that vision technology will be more applied across a broad range of business and consumer products. This will result in a strong industry demand for computer vision engineers—for people who understand vision technology and know how to apply it in real-world problems.

Outcomes

Students are able to (1) explain computer vision problems in writing; (2) write MATLAB code to solve computer vision problems; (3) describe the theories and principles in computer vision; (4) conduct independent research on a chosen research topic, write a small research report, and give an oral presentation; (5) demonstrate logical thinking and problem-solving skills; (6) process images in both the spatial and frequency domains; (7) explain the technical theory behind formation of images; and (8) critique various methodologies for solving problems in computer vision and image processing.

Assessment

Indicative assessments in this unit are as follows: (1) laboratory solutions (5% per lab); (2) research project; and (3) final exam. Further information is available in the unit outline.

For units commencing in May 2022 or later the availability of the supplementary assessment is subject to confirmation.

Student may be offered supplementary assessment in this unit if they meet the eligibility criteria.

Except where supplementary assessment is not available in a unit, it will be offered to students in all units who:

• Are in good academic standing overall;
• Have passed over half the units taken in the teaching period concerned, except where they are only enrolled in two or less units in the period;
• Have submitted all assessment items in the unit;
• Have achieved a mark between 45 and 49 for the unit overall, or the same mark in any failed component item in the unit; and
• No finding of academic misconduct has been made against them in the unit concerned.

Additionally student may apply for supplementary assessment in any unit which is the final unit required for graduation in there course and where they have achieved a mark between 45 and 49 for the unit overall, or the same mark in any failed component item in the unit.

Unit Coordinator(s)

Professor Mohammed Bennamoun

Unit rules

Prerequisites:

Enrolment in in the ( HON-CMSSE Computer Science and Software Engineering [Honours] or the 62530 Master of Data Science or the 63550 Master of Engineering ) or ( the 62550 Master of Professional Engineering and the SP-EBIOM Biomedical Engineering specialisation or the SP-EELEC Electrical and Electronic Engineering specialisation or the SP-ESOFT Software Engineering specialisation ) or ( the 53560 Master of Physics and the SPSP-MEDPH Medical Physics specialisation ) or ( the BH008 Bachelor of Advanced Computer Science [Honours] and the MJD-ARIDM Artificial Intelligence major ) or ( the BH011 Bachelor of Engineering [Honours] and the MJD-EAUTO Automation and Robotics Engineering major )

Co-requisites:

Nil

Advisable prior study:

CITS2401 Computer Analysis and Visualisation And MATH1012 Mathematical Theory and Methods (Note: Students must have the ability to program in a high-level programming language and the ability to reason in linear algebra and calculus.)

Incompatibility:

Nil