Registry
Module Specifications
Archived Version 2005 - 2006
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| Module Aims | |||||||||||||||||||||||||||||||||
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This module will concentrate on developing the fundamentals necessary to design and develop a wide range of imaging solutions. Such solutions relate to the fields of computer and machine vision, video data processing, imaging graphics, imaging science, multimedia and enhanced reality systems.This module will make extensive use of the NeatVision image analysis development environment to reinforce all the issues covers during the lectures.
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| Learning Outcomes | |||||||||||||||||||||||||||||||||
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On completion of this module, the student will be able to · Recall, review and analyse the essential algorithms, methodologies and techniques involved in image processing & analysis. (PO1, PO2)· Illustrate their ability to comprehend and interpret issues relating to the design of image processing & analysis techniques. (PO1, PO2, PO3, PO5, PO6)· Synthesize and evaluate the relevant merits of competing image processing & analysis techniques. (PO1, PO5)· Apply image processing & analysis techniques in a range of application scenarios. (PO1, PO2, PO3, PO5, PO6)
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Assume that a 0 credit module load represents approximately 75 hours' work, which includes all teaching, in-course assignments, laboratory work or other specialised training and an estimated private learning time associated with the module. | |||||||||||||||||||||||||||||||||
| Indicative Syllabus | |||||||||||||||||||||||||||||||||
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· Introduction | |||||||||||||||||||||||||||||||||
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| Indicative Reading List | |||||||||||||||||||||||||||||||||
| Recommended text:· Image Processing, Analysis and Machine Vision, M. Sonka, V. Hlavac and R. Boyle (1993), Chapman & Hall. Additional texts:· Fundamentals of Digital Image Processing. Jain, A.K. (1989), Prentice-Hall.· On-line Internet teaching resources. | |||||||||||||||||||||||||||||||||
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Contribution to Programme Areas:
Science & Mathematics Discipline - specific Technology Information and Communications Technology Design and Development Engineering Practice Social and Business Context 3 4 3 4 4 1 Contribution to Programme Outcomes:
Knowledge and Its Application:
The ability to derive and apply solutions from a knowledge of sciences, engineering sciences, technology and mathematics Problem Solving:
The ability to identify, formulate, analyse and solve engineering problems; Design:
The ability to design a system, component or process to meet specified needs, to design and conduct experiments and to analyse and interpret data; Ethical Practice:
An understanding of the need for high ethical standards in the practice of engineering, including the responsibilities of the engineering profession towards people and the environment Effective Work and Learning:
The ability to work effectively as an individual, in teams and in multidisciplinary settings together with the capacity to undertake lifelong learning; Effective Communication:
The ability to communicate effectively with the engineering community and with society at large 4 4 4 1 3 2 Teaching & Learning Strategies/Assessment Methodology:
This module is presentment in a traditional (lecture and continuous assessment) with significant online support. Selected examples illustrating key concepts are also presented along with their associated images/data. The course makes use of the NeatVision visual programming-based computer vision development environment to keep the students focus on the issues relating to image processing & analysis design rather than programming.
Additional online resources are employed where appropriate.
A significant element of this module is based on a problem based learning methodology using class examples and case studies in conjunction with two project assignments as part of the continuous assessment element of this module. | |||||||||||||||||||||||||||||||||
| Programme or List of Programmes | |||||||||||||||||||||||||||||||||
| EE | BEng in Electronic Engineering | ||||||||||||||||||||||||||||||||
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