CSMIA19-Image Analysis

Module Provider: Computer Science
Number of credits: 10 [5 ECTS credits]
Level:7
Terms in which taught: Autumn / Summer term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded: CS3IA16 Image Analysis
Current from: 2021/2

Module Convenor: Dr Hong Wei
Email: h.wei@reading.ac.uk

Type of module:

Summary module description:

The module delivers a set of topics involved in image analysis, such as image enhancement, image compression, image segmentation, and colour image processing. Relevant techniques are introduced in lectures and practised in assigned lab-based coursework.ÌýÌý

Aims:

The module aims to provide students with theoretical and practical knowledge of digital image processing and analysis from various techniques and applications.

This module also encourages students to develop a set of professional skills, such as problem solving; critical analysis of published literature; creativity; technical report writing for technical and non-technical audiences; self-reflection; and effective use of commercial software. Research elements are built into the coursework assignment to enhance students’ research studies.

Assessable learning outcomes:

Students who complete this module will have:

• basic skills for image analysis;


• the ability to address issues associated with techniques of image transformation, histogram analysis and modification, image morphological operations and colour image manipulation;


• skills to develop algorithms for digital image enhancement, image compression and texture-based image segmentation.


• skill of critical analysis existing techn iques and decision making in solving a real-world problem.

This module will be assessed to a greater depth than the excluded module CS3IA16.

Additional outcomes:

Programming skills can be improved from coursework assignments, which associate with practical assignments.Ìý Research studies are also involved in coursework assignments.

Outline content:

The module covers the following topics.

• digital image fundamentals;


• image enhancement in the spatial domain;


• image enhancement in the frequency domain;


• colour image processing;


• mathematical morphology in image processing;


• image compression;


• image segmentation.

Brief description of teaching and learning methods:

Lectures supported by tutorials and laboratory practicals.