Computer and Machine Vision
Prof. John Ringwood
7.5 ECTS credits
Linear algebra, geometry, programming skil
ls (C, MATLAB)
To introduce the student to the theory, applications and techniques of
computer and machine vision. To provide students with an understanding of
the problems involved in the development and implementation
Having successfully completed this course, the student will:
* Be familiar with the essential elements of machine vision systems.
* Have the ability to design and implement image processing, analysis and
have a knowledge of the performance of commercial vision systems.
* be able to evaluate emerging computer and machine vision technologies.
Cardiovascular modeling, Muscle Models, Blood pressure regulat
auditory and visual systems modelling.
Time Allowance for Constituent Elements
Sensors, Optics & Lighting; Image Representation
Point Operations; Neighbourhood Operations
Feature Extraction; Image Analysis
3D Imaging Techniques
Industrial Case Studies
Elements and Forms of Assessment
Assignments (3 at 25% each)
Any plagiarism results in expulsion from programme.
Pass Standard and any Special
Requirements for Passing Modules:
students are not
required to pass the examined and continuous components separately
an overall pass mark of 40% is
David A. Forsyth, Jean Ponce
er Vision: A Modern Approach,
Linda Shapiro, George Stockman
Programmes currently utilising module
ME in Electronic Engineering