Registry

Module Specifications

Archived Version 2013 - 2014

Module Title	Image Processing & Analysis with Project
Module Code	EE453
School	School of Electronic Engineering
Online Module Resources
Module Co-ordinator	Prof Paul F. Whelan	Office Number	S362
NFQ level	8	Credit Rating	7.5
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

Description

Most people are familiar with the concept of processing an image to improve its quality or the use of image analysis software tools to make basic measurements; but what are the ideas behind such solutions and why is knowledge of these concepts important in developing successful computer vision applications? This module will answer these questions by focusing on both the theoretical, mathematical and practical issues associated with a wide range of computer vision solutions. Such solutions relate to the fields of image processing & analysis, industrial/machine vision, video data processing, biomedical engineering, imaging science, sensor technology, multimedia and enhanced reality systems. This module will concentrate on developing the fundamentals necessary to design, develop and understand a wide range of basic imaging processing (image to image), image analysis (image to feature), image classification (feature to decision), performance characterisation (data to quantitative performance indicators) and computer vision (image to interpretation) solutions. All solutions have limitations and a key element of this module is to focus on how to approach the design, testing and evaluation of successful computer vision applications within an engineering framework. This module will make extensive use of an image analysis development environment to reinforce all the issues covers during the lectures. In addition to the common elements associated with EE425, this module will contain a significant competitive group image processing & analysis project. Students will have the opportunity to develop a commercial level solution in one of two areas: biomedical or industrial computer vision. The focus of the project will be on developing engineering solutions rather than a research projects. Students will be expected to submit individual independent reports (of a fixed length) to be presented in the form of a technical paper communication. In addition to the engineering issues, the report must outline both the commercial potential and the ethical issues involved with the work.

Learning Outcomes

1. Recall, review and analyse the essential theories, algorithms, methodologies and techniques involved in computer vision.
2. Illustrate their ability to comprehend and interpret issues relating to the design of image processing & analysis techniques.
3. Synthesize and evaluate the relevant merits of competing computer vision techniques.
4. Apply computer vision techniques in a range of application scenarios.
5. Develop an understanding of the engineering issues involved in the commercial development of image processing and analysis solutions.
6. Illustrate the ability to place a vision engineering project in the context of both commercial and ethical realities.
7. Communicate technical and non technical issues in a group based environment.

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Lecture	36	This module is presented in a traditional format (lecture and continuous assessment) with significant practical support [including: long-format electronic notes and associated course text, pdf versions of the class slides, mailing list support, computer vision development environment (used for the assignments and to illustrate computer vision concepts), self assessment questions and selected examples illustrating key concepts are also presented along with their associated images/data].
Assignment Completion	30	Pratical assignments
Directed learning	62.5	Project
Independent Study	3	End of Semester Exam
Independent Study	20	Online activity with module material
Independent Study	36	General revision and practice
Total Workload: 187.5

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Introduction; Tutorial on course tools

Image Representation
File Formats; Point Operations; Neighbourhood Operations, Distance Transform

Feature Extraction; Image Analysis; Local Operators

Image Classification (1)

Global Image transforms
Geometric,Hough, DFT, DCT

Mathematical Morphology (1)
Binary and Grey Scale

Colour Image Processing & Analysis (1)

Texture Analysis (1)

Interest Point Detection

Image Acquisition
Optics, Lighting and Sensors

Performance Analysis

Systems Engineering

Case Studies

Ethics

Sample Problems & Review

Project

Assessment Breakdown
Continuous Assessment	50%	Examination Weight	50%

Type	Description	% of total	Assessment Date
Course Work Breakdown

Reassessment Requirement
Resit arrangements are explained by the following categories; 1 = A resit is available for all components of the module 2 = No resit is available for 100% continuous assessment module 3 = No resit is available for the continuous assessment component
Unavailable

Indicative Reading List

Paul F. Whelan, Derek Molloy,: 2000, Machine Vision Algorithms in Java, Springer, 1-85233-218-2
Milan Sonka, Vaclav Hlavac, and Roger Boyle: 2008, Image processing, analysis, and machine vision, Thompson Learning, Toronto, 978-0495082521
E. R. Davies: 0, Machine vision, 0122060938]
Paul F Whelan: 2010, Online Course long form and class notes (slides),
Rafael C. Gonzalez, Paul Wintz: 1987, Digital image processing, Addison-Wesley, Reading, Mass., 0201110261]
Rafael C. Gonzalez, Richard E. Woods: 1992, Digital image processing, Addison-Wesley, Reading, Mass., 0201508036]
Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins,: 0, Digital Image Processing Using MATLAB, 2nd ed., 0982085400]

Other Resources

1179, Module Website, Paul F Whelan, 2010, EE453 & EE425, http://elm.eeng.dcu.ie/~whelanp/ipa/protected_material/ipa_notes.html, 1180, Module Software, Paul F Whelan, 2010, VSG Image Processing & Analysis Toolbox (VSG IPA TOOLBOX), http://www.cipa.dcu.ie/code.html, 1181, Websites:, 0, Online Image Processing References,

Programme or List of Programmes

BMED	B.Eng. in Biomedical Engineering
DME	B.Eng. in Digital Media Engineering
ECSAO	Study Abroad (Engineering & Computing)
EE	BEng in Electronic Engineering
EEV	M.Eng. in Electronic Engineering
MEN	MEng in Electronic Systems
MEQ	Masters Engineering Qualifier Course
MTC	MEng in Telecommunications Engineering
SMPEC	Single Module Programme (Eng & Comp)

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