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Unit of study_
AMME4710: Computer Vision and Image Processing
2024 unit information
This unit of study introduces students to vision sensors, computer vision analysis and digital image processing. This course will cover the following areas: fundamental principles of vision sensors such as physics laws, radiometry, CMOS/CDD imager architectures, colour reconstruction; the design of physics-based models for vision such as reflectance models, photometric invariants, radiometric calibration. This course will also present algorithms for video/image analysis, transmission and scene interpretation. Topics such as image enhancement, restoration, stereo correspondence, pattern recognition, object segmentation and motion analysis will be covered.
Unit details and rules
Managing faculty or University school:
Engineering
| Study level | Undergraduate |
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| Academic unit | Aerospace, Mechanical and Mechatronic |
| Credit points | 6 |
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Prerequisites:
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30cp of any 3000- or higher level Engineering units of study and (ENGG1801 or ENGG1810 or INFO1110 or INFO1910) |
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Corequisites:
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None |
| Prohibitions:
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None |
| Assumed knowledge:
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The unit assumes that students have strong skills in either MATLAB or Python |
At the completion of this unit, you should be able to:
- LO1. demonstrate skills in presenting a final design solution to a computer vision/image processing problem
- LO2. demonstrate skills in working on a design project within a team including communicating with team members, planning, and managing tasks
- LO3. design an engineering solution to a given image processing task by selecting, developing and evaluating appropriate algorithms and techniques.
- LO4. understand the fundamental principles of how images are formed including the basics of image sensors, radiometry, colour, and projective geometry
- LO5. apply basic techniques in image processing including the use of image filtering, features, edge detection, colour spaces/transforms, and matching
- LO6. apply advanced techniques in computer vision including stereo vision, 3D mapping, object detection, image classification, and use of machine learning algorithms in vision
- LO7. apply a wide range of image processing techniques to real world applications
- LO8. understand the type of algorithm required for a particular image processing task.
Unit availability
This section lists the session, attendance modes and locations the unit is available in. There is a unit outline for each of the unit availabilities, which gives you information about the unit including assessment details and a schedule of weekly activities.
The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.
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Modes of attendance (MoA)
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