University of Sussex / s

Title

/

Machine Vision

Code / DGM01
Level / 7 (Masters level)
Credit rating / 15 7-level credits
Prerequisites / None
Type / Single (taught) module
Aims / To provide the student with an introduction to the rapidly developing and exciting field of machine vision. This wide-ranging field of study is concerned with the automated analysis of images, in order to reach some form of understanding of the scene from which those images were derived.
Learning outcomes/objectives / On successful completion of the module the student should be able to:
[1]clearly understand and appraise the interrelationships of the disciplines which underpin machine vision
[2]understand and appraise the key elements in machine vision systems
[3]relate the theoretical treatment of the subject matter to practical applications in industrial machine vision
[4]undertake sufficient in-depth personal research in order to prepare a dissertation on a detailed investigation into a relevant subject area which extends significantly beyond the material taught in the module.
Content /
  • Scene Constraints.
  • Image Acquisition.
  • Image Processing.
  • Segmentation.
  • Feature Extraction.
  • Pattern Classification.
  • Industrial Machine Vision.

Teaching and learning strategies / Lectures, tutorials, laboratory work, industrial case studies and personal research.
Learning support / Use of the School of Engineering’s computer laboratories with the ImageJ open-sourceimage processing package. Use of Learning Resources facilities at both Institutions to support research into dissertation topic.
Primary Course Text:
  • Awcock, G., and Thomas, R; “Applied Image Processing”, Macmillan New Electronics, 1995. ISBN 0070014701.NB: This text is now out of print, but a continuously updated version is made available to students via studentcentral
Indicative Supplementary Reading:
  • Gonzalez, R. and Woods, R; “Digital image processing”, 2nd Edition, Upper Saddle River, N.J. :Prentice Hall ;London :Pearson Education,c2002. ISBN 0201180758
DGM01 – Machine Vision - Additional module support.
Assessment / End-of-course examination ([1], [2], [3]), 60% weighting; coursework consisting of a self-study dissertation ([3], [4]), 40% weighting.
Brief description of module and/or aims / Vision is the most versatile sense in animate beings, and artificial vision is actively sought to confer flexibility on machines and to solve a wide variety of real-world problems. This modules aims to provide students with a holistic and pragmatic introduction to this field, and to give them a solid grounding in the disciplines involved in implementing the solution of problems based on the utilisation of data sensed in the form of images.
Area examination boards / Digital Electronics
Module team/authors / Dr G. J. Awcock and Dr. D. H. Lawrence
Semester offered / Autumn Term with examination at beginning of Spring term.
Date of first approval / September 1994
Date of last revision / February 2005
Date of approval of this version / May 2006 at the BrightonSchool of EngineeringSchool Board
Version number / 3.0.1
Replacement for previous module / None
Field for which module is acceptable and status in that field / Digital Electronics
Course(s) for which module is acceptable and status in course / PgCert in Digital Systems (DS)/DE; - optional
PgDip in DE/DS/DEC/PDS; - optional
MSc Digital Electronics (DE); - compulsory
MSc in Digital Electronics and Communication (DEC); - compulsory
MSc in Programmable Digital Systems (PDS); - compulsory
School Home / School of Engineering at University of Brighton
External examiner / Dr. Mike Shaw, JohnMooresUniversity, Liverpool

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