The module introduces fundamental techniques employed in image processing and pattern recognition providing an understanding of how practical pattern recognition systems may be developed able to address the inherent difficulties present in real world situations. The material is augmented with a study of biometric and security applications looking at the specific techniques employed to recognise biometric samples.
Total contact hours: 33
Private study hours: 117
Total study hours: 150
Method of assessment
• Fairhurst, Michael Christopher (1988) Computer vision for robotic systems: an introduction, Prentice Hall, London, New York.
• Solomon, Chris (2011) Fundamentals of digital image processing : a practical approach with examples in Matlab. Wiley-Blackwell.
• Duda, Richard O.; Hart, Peter E.; Stork, David G. (2000) Pattern Classification, John Wiley and Sons.
• Picton, Phil. (2000) Neural Networks. 2nd edition. Palgrave, Basingstoke.
• Graupe, Daniel. (2019) Principles of Artificial Neural Networks – Basic Designs to Deep Learning. 4th Edn. World Scientific Publishing.
• Jain, Anil, Ross, Arun, Nandakumar, Karthik. (2011). Introduction to Biometrics. Springer.
• Jain, Anil, Flynn, Patrick, Ross, Arun (eds.). (2008). Handbook of Biometrics. Springer.
See the library reading list for this module (Canterbury)
1. An understanding of three main integrated themes:
(i) basic image processing (representation, transformation, extraction of key information from images);
(ii) image analysis (automatic interpretation of images and pattern recognition methodology) and
(iii) computational architectures for image analysis (especially neural network structures).
2. A familiarity with fundamental algorithms underpinning modern image analysis systems.
3. Experience of the requirements for implementing algorithms for image analysis.
4. A practical experience of working with typical algorithms and architectures.
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Credit level 5. Intermediate level module usually taken in Stage 2 of an undergraduate degree.
- ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
- The named convenor is the convenor for the current academic session.
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