Module overview
This module is useful to introduce:
- Image processing and its relation to signal processing.
- Image transformations for filtering, coding and etc.
- Histogram processing algorithms to enhance image qualities and visibility.
- Theories analysing and understanding images using feature extraction, segmentation, and texture modelling.
- Linear and nonlinear methods for shape registration, noise reduction and restoration.
- Image classification and object recognition.
- Edge detection
Aims and Objectives
Learning Outcomes
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- How images can be digitised and stored in computers
- How computers can process digital images
- The relation to signal processing and other fields
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- How to extract features from images
- How to do linear and nonlinear filtering on images
- What segmentation is and how to do segmentation in digital images
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- How to use features to classify images for recognition
Syllabus
- Overview [1]
- Image acquisition and sampling theory [1]
- Image transformations [2]: Fourier, Discrete Cosine and Wavelet
- Histogram processing and linear filtering [1]
- Point processing and operations [1]
- Calculus of variations and Lagrange miltipliers [2]
- Active contours [4]: Kass Model and Level Set formulation
- Geodesic Active contours [2]
- Shape Registeration [1]
- Image noise reduction[1]
- Anisotropic Diffusion [1]
- Image Restoration [3]: Wiener Filter and total variation
- Shape description [3]
- Image Classifcation and Recognition[1]
Learning and Teaching
| Type | Hours |
|---|---|
| Supervised time in studio/workshop | 24 |
| Wider reading or practice | 50 |
| Lecture | 24 |
| Revision | 10 |
| Follow-up work | 12 |
| Preparation for scheduled sessions | 12 |
| Completion of assessment task | 18 |
| Total study time | 150 |
Resources & Reading list
Textbooks
Nixon M S and Aguado A S (2012). Feature Extraction and Image Processing. Academic Press.
W.K. Pratt (1991). Digital Image Processing. John Wiley.
R.C. Gonzalez, R.E. Woods (2008). Digital Image Processing. Pearson International Edition.
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Final Assessment | 70% |
| Continuous Assessment | 30% |
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