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Unit information: Image Processing and Computer Vision in 2016/17

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Image Processing and Computer Vision
Unit code COMS30121
Credit points 10
Level of study H/6
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Professor. Calway
Open unit status Not open
Pre-requisites

COMS10001 and COMS10002 or equivalent programming experience

Co-requisites

None

School/department Department of Computer Science
Faculty Faculty of Engineering

Description

The aim of this unit is to give you an introduction to computational vision: the theory, principles, techniques, algorithms and applications. The unit is structured in terms of topics, each associated to a lecture, follow-up seminar, laboratory sessions and self-study. For each topic, we will cover the underlying theory, the practical challenges, important algorithms and example applications. Practical implementation work will be conducted alongside in small groups throughout the unit using for instance C/C++ and OpenCV.

Intended learning outcomes

At the end of the unit you will understand and be able to apply basic theoretical concepts and practical techniques used in image processing and computer vision. Laboratory classes and project work will have exposed you to technology and software used in image analysis and manipulation.

Teaching details

A weekly lecture, seminar and labs (which should be at least 2 hours long)

Assessment Details

Examination 50%, Practical Assignments 50%

Reading and References

- Forsyth, David A., and Jean Ponce. Computer Vision: A Modern Approach (2003).

- Sonka, Milan, Vaclav Hlavac, and Roger Boyle. Image processing, analysis, and machine vision. Cengage Learning, (2014).

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