Module overview
Aims and Objectives
Learning Outcomes
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- Current approaches to image formation and image modelling
- Human and computer vision systems
- Current approaches to basic image processing and computer vision
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Analyse and design a range of algorithms for image processing and computer vision
- Develop and evaluate solutions to problems in computer vision
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- Implement basic image processing algorithms
Syllabus
Learning and Teaching
Type | Hours |
---|---|
Follow-up work | 12 |
Tutorial | 12 |
Completion of assessment task | 25 |
Wider reading or practice | 55 |
Lecture | 24 |
Preparation for scheduled sessions | 12 |
Revision | 10 |
Total study time | 150 |
Resources & Reading list
Textbooks
Sonka, Hlavac & Boyle (2008). Image Processing, Analysis and Machine Vision. PWS Publishing.
Stockman and Shapiro (2001). Computer Vision. Prentice Hall.
Nixon, M.S. and Aguado, A.S. (2012). Feature Extraction & Image Processing. Academic Press.
Gonzalez et al (2008). Digital Image Processing. Pearson.
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
Method | Percentage contribution |
---|---|
Continuous Assessment | 40% |
Final Assessment | 60% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
Method | Percentage contribution |
---|---|
Set Task | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
Method | Percentage contribution |
---|---|
Set Task | 100% |
Repeat Information
Repeat type: Internal & External