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The University of Southampton
Courses

ELEC6213 Image Processing

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 Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • How to use features to classify images for recognition
Subject Specific Practical Skills

Having successfully completed this module you will be able to:

  • How to do linear and nonlinear filtering on images
  • How to extract features from images
  • What segmentation is and how to do segmentation in digital images

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

TypeHours
Supervised time in studio/workshop24
Completion of assessment task18
Preparation for scheduled sessions12
Revision10
Follow-up work12
Lecture24
Wider reading or practice50
Total study time150

Resources & Reading list

R.C. Gonzalez, R.E. Woods (2008). Digital Image Processing. 

Nixon M S and Aguado A S (2012). Feature Extraction and Image Processing. 

W.K. Pratt (1991). Digital Image Processing. 

Assessment

Summative

MethodPercentage contribution
Examination  (2 hours) 70%
Laboratory 30%

Repeat

MethodPercentage contribution
Examination 100%

Referral

MethodPercentage contribution
Examination  (2 hours) 100%

Repeat Information

Repeat type: Internal & External

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