Print View: ELEC7602 - Sem 1 2008 - St Lucia

1. General Course Information

1.1 Course Details

Course Code: ELEC7602 Course Title: Signal & Image Processing II
Coordinating Unit: School of Information Technology and Electrical Engineering
Semester: Semester 1, 2008 Mode: Internal
Level: Postgraduate Coursework
Location: St Lucia
Number of Units: 2 Contact Hours Per Week: 3L1T1P
Pre-Requisites: (ELEC3600 or ELEC7601) + STAT2202
Incompatible: ELEC4600 or ELEC7602 or 3E413

Course Description: Advanced digital filtering: polyphase, multirate, all-pass, & IIR filters. Signal conditioning, analog filter types, sigma delta converters. Fast algorithms; Cooley-Tukey FFT, mixed radix formulations, Good-Thomas algorithm. Computer vision, morphological techniques, watershed transform, skeletonisation, image segmentation, active contours.

Assumed Background:

Recommended Prerequisites: (ELEC3600/ELEC7601) + (STAT2202)

Prerequisites may not be necessary for good students as much of the ELEC4600 material is self-contained. Some C/C++ and MATLAB coding background would be very helpful. Knowledge of Fourier transforms, signal and systems theory, basic digital filters, probability theory, and linear algebra is assumed.

1.2 Course Introduction

Signal and Image processing engineers are premium specialists in ICT. These engineers may be seen as a discipline emerging in the overlap between Electrical Engineering and Computer Science. Typically such graduates would be characterized by very strong mathematical backgrounds, hardware familiarity, excellent coding skills, and outstanding knowledge of signal and image processing techniques.

Such skills are in high demand to support 21^st century high technology companies based on automatically extracting information from the world of images, sound, and video rather than text and numbers as was done in the 20^th century. Graduates may work in diverse areas such as array processing, supercomputing, data mining, computer vision, pattern recognition, biometric security, computer-based medical image analysis, and intelligent CCTV (closed circuit TV). This course addresses many of the core skills necessary for the extraction of knowledge from ever increasing amounts of raw noisy data.

1.3 Course Staff

Course Coordinator: Brian Lovell
Phone: 33654134 Email: lovell@itee.uq.edu.au Homepage: www.itee.uq.edu.au/~lovell
Campus: St Lucia Building: General Purpose South (Map) Room: 533
Consultation:

Academic staff are extremely busy. They need to supervise many postgraduate and undergraduate thesis project students, write grants, talk to industry, write research papers, develop curricula, write course material and place it on the websites, deliver seminars, and handle innumerable enquiries. While your major contact with academics is in the undergraduate teaching environment, undergraduate teaching often only represents about 30% of an academic's workload. Many of these tasks require long periods of uninterrupted concentration. Answering the office door or taking a phone call for random student enquiries is therefore very disruptive and saps creative energy. Most enquiries are better handled by email at a convenient time to staff, or immediately before or after formal contact hours.

So, in general, consult me by the following methods in order of preference:

See me immediately before or after scheduled contact hours at the teaching venue
Email me anytime (consult the course newsgroup and website first to see if your question has already been addressed)
If a student really needs to see me, they should email for an appointment, and see me at a mutually agreed time (generally in my consultation hour).

PLEASE DO NOT KNOCK ON MY DOOR UNLESS YOU HAVE BOOKED AN APPOINTMENT FIRST.

1.4 Timetable

Timetables are available on mySI-net.

Additional Timetable Information

Teaching Plan

Exact timing subject to change due to travel comitments and availability of guest lecturers

Week Number	Lecture Number	Lecture Topic	Tut/Prac Session	Assessment
1	1	Multirate Filtering 1
1	2	Multirate Filtering 2
2	3	Fast Fourier Transform 1	Tutorial 1: Multirate filtering	Hand in assignment
2	4	Fast Fourier Transform 2	Tutorial 1: Multirate filtering	Hand in assignment
3	5	IIR Filters
3	6	All Pass Filters
4	7	Image Processing 1- Introduction	Tutorial 2: Fast Fourier Transform	Hand in assignment
4	8	Image Processing 2 - Edge Detection	Tutorial 2: Fast Fourier Transform	Hand in assignment
5	9	Image Processing 3 -Graph Based Approaches, Viterbi
5	10	Cell Image Segmentation - Application
6	11	Image Processing 4 - Thresholding	Tutorial 3: Edge Detectors	Hand in assignment
6	12	Image Processing 5 - Temporal Filtering	Tutorial 3: Edge Detectors	Hand in assignment
7	13	Image Processing 6 - Binary Morphology
7	14	Image Processing 7 - Morphological Operators 1
8	15	Image Processing 8 - Morphological Operators 2	Tutorial 4: Image Analysis	Hand in assignment
8	16	Image Processing 9 - Grayscale Morphology	Tutorial 4: Image Analysis	Hand in assignment
9	17	Image Processing 10 - Morphological Cell Segmentation
9	18	Image Processing 11 - Image Compression
10	19	Image Processing 12 - Colour Coordinate Systems	Tutorial 5: Image Analysis	Hand in assignment
10	20	Advanced Techniques - UQ Research problems	Tutorial 5: Image Analysis	Hand in assignment
11	21	Advanced Techniques - UQ Research problems
11	22	Face Recognition with eigen faces
12	23	Guest lectures
12	24	Guest lectures
13	25	Guest lectures
13	26	Revision and Closing
	Revision Period
Exam Week 1				Final Exam
Exam Week 2				Final Exam

5. Assessment

5.1 Assessment Summary

This is a summary of the assessment in the course. For detailed information on each assessment, see 5.5 Assessment Detail below.

Assessment Task	Due Date	Weighting	Learning Objectives
Literature Review Biometric Security	25 Feb 08 09:00 - 30 May 08 17:00	Equally Weighted	2
Problem Solution Assignment 1	7 Mar 08 14:00 - 21 Mar 08 17:00	Equally Weighted	1, 3, 4
Problem Solution Assignment 2	21 Mar 08 14:00 - 4 Apr 08 17:00	Equally Weighted	1, 3, 4
Problem Solution Assignment 3	4 Apr 08 14:00 - 21 Apr 08 17:00	Equally Weighted	1, 2, 3, 4
Problem Solution Assignment 4	25 Apr 08 14:00 - 9 May 08 17:00	Equally Weighted	1, 2, 3, 4
Problem Solution Assignment 5	9 May 08 14:00 - 23 May 08 17:00	Equally Weighted	1, 2, 3, 4, 5
Exam - during Exam Period (Central) Final Exam	Examination Period	30%	2, 3, 5

5.2 Course Grading

Grade 1, Fail: Fails to demonstrate most or all of the basic requirements of the course:

<20% overall

Grade 2, Fail: Demonstrates clear deficiencies in understanding and applying fundamental concepts; communicates information or ideas in ways that are frequently incomplete or confusing and give little attention to the conventions of the discipline:

>=20% but <45% overall

Grade 3, Fail: Demonstrates superficial or partial or faulty understanding of the fundamental concepts of the field of study and limited ability to apply these concepts; presents undeveloped or inappropriate or unsupported arguments; communicates information or ideas with lack of clarity and inconsistent adherence to the conventions of the discipline:

>=45% but <50% overall

Grade 4, Pass: Demonstrates adequate understanding and application of the fundamental concepts of the field of study; develops routine arguments or decisions and provides acceptable justification; communicates information and ideas adequately in terms of the conventions of the discipline:

>=50% but <65% overall

Grade 5, Credit: Demonstrates substantial understanding of fundamental concepts of the field of study and ability to apply these concepts in a variety of contexts; develops or adapts convincing arguments and provides coherent justification; communicates information and ideas clearly and fluently in terms of the conventions of the discipline:

>=65% but <75% overall

Grade 6, Distinction: As for 5, with frequent evidence of originality in defining and analysing issues or problems and in creating solutions; uses a level, style and means of communication appropriate to the discipline and the audience:

>=75% but <85% overall

Grade 7, High Distinction: As for 6, with consistent evidence of substantial originality and insight in identifying, generating and communicating competing arguments, perspectives or problem solving approaches; critically evaluates problems, their solutions and implications:

>=85% overall

Other Requirements & Comments :

Each passing grade subsumes and goes beyond the grades lower than it. At the discretion of the lecturers, final grades may be scaled upwards but not decreased.

5.3 Late Submission

No extensions will be granted except in exceptional personal circumstances (documented medical reason or family emergency). Personal hardware or computer failures are not grounds for extension.

5.4 Other Assessment Information

None

5.5 Assessment Detail

Biometric Security

Type: Literature Review
Learning Objectives Assessed: 2
Due Date:
25 Feb 08 09:00 - 30 May 08 17:00
Weight: Equally Weighted
Task Description: By critically examining the literature describe and contrast the theory, practice, and performance of two non-biological biometric authentication/recognition methods not covered in lectures. You may consider 3D face, iris, hand geometry, fingerprinting, voice etc. Aim for a 15 page report including all figures and bibliography.
Criteria & Marking: Expert judgement and ranking based on past student reports.

Assignment 1

Type: Problem Solution
Learning Objectives Assessed: 1, 3, 4
Due Date:
7 Mar 08 14:00 - 21 Mar 08 17:00
Weight: Equally Weighted
Task Description: Mutirate Filtering
Criteria & Marking:

Computer assignments may be assessed by computer for plagiarism. Only original code will receive full marks. Assignments will generally be handed back to students two weeks after (possibly extended) submission date. The assignments will reinforce learning by asking students to apply material taught in lectures to tutorial assignments. Coding skills will be developed in the supervised tutorial/practical sessions. Formal coding skills will not be taught, although specific questions will be answered. Students must use the relevant on-line manuals and tutorials to acquire specific coding knowledge.

Solid attempts to answer the questions will generally receive at least 50%
Good attempts will generally receive up to 75%
Some degree of originality and flair will generally be required to achieve above 75%

Assignment 2

Type: Problem Solution
Learning Objectives Assessed: 1, 3, 4
Due Date:
21 Mar 08 14:00 - 4 Apr 08 17:00
Weight: Equally Weighted
Task Description: Fast Fourier Transforms
Criteria & Marking: Computer assignments may be assessed by computer for plagiarism. Only original code will receive full marks. Assignments will generally be handed back to students two weeks after (possibly extended) submission date. The assignments will reinforce learning by asking students to apply material taught in lectures to tutorial assignments. Coding skills will be developed in the supervised tutorial/practical sessions. Formal coding skills will not be taught, although specific questions will be answered. Students must use the relevant on-line manuals and tutorials to acquire specific coding knowledge.

Solid attempts to answer the questions will generally receive at least 50%
Good attempts will generally receive up to 75%
Some degree of originality and flair will generally be required to achieve above 75%

Submission: Submission of the assignments will be via the submission boxes on level one of the GPSouth building. Your assignment submission must be accompanied by a signed coversheet declaring that the submission is your original work.

Assignment 3

Type: Problem Solution
Learning Objectives Assessed: 1, 2, 3, 4
Due Date:
4 Apr 08 14:00 - 21 Apr 08 17:00
Weight: Equally Weighted
Task Description: Image Processing
Criteria & Marking: Computer assignments may be assessed by computer for plagiarism. Only original code will receive full marks. Assignments will generally be handed back to students two weeks after (possibly extended) submission date. The assignments will reinforce learning by asking students to apply material taught in lectures to tutorial assignments. Coding skills will be developed in the supervised tutorial/practical sessions. Formal coding skills will not be taught, although specific questions will be answered. Students must use the relevant on-line manuals and tutorials to acquire specific coding knowledge.

Solid attempts to answer the questions will generally receive at least 50%
Good attempts will generally receive up to 75%
Some degree of originality and flair will generally be required to achieve above 75%

Assignment 4

Type: Problem Solution
Learning Objectives Assessed: 1, 2, 3, 4
Due Date:
25 Apr 08 14:00 - 9 May 08 17:00
Weight: Equally Weighted
Task Description: Stereo matching
Criteria & Marking: Computer assignments may be assessed by computer for plagiarism. Only original code will receive full marks. Assignments will generally be handed back to students two weeks after (possibly extended) submission date. The assignments will reinforce learning by asking students to apply material taught in lectures to tutorial assignments. Coding skills will be developed in the supervised tutorial/practical sessions. Formal coding skills will not be taught, although specific questions will be answered. Students must use the relevant on-line manuals and tutorials to acquire specific coding knowledge.

Solid attempts to answer the questions will generally receive at least 50%
Good attempts will generally receive up to 75%
Some degree of originality and flair will generally be required to achieve above 75%

Assignment 5

Type: Problem Solution
Learning Objectives Assessed: 1, 2, 3, 4, 5
Due Date:
9 May 08 14:00 - 23 May 08 17:00
Weight: Equally Weighted
Task Description:

Real world problems

Criteria & Marking: Computer assignments may be assessed by computer for plagiarism. Only original code will receive full marks. Assignments will generally be handed back to students two weeks after (possibly extended) submission date. The assignments will reinforce learning by asking students to apply material taught in lectures to tutorial assignments. Coding skills will be developed in the supervised tutorial/practical sessions. Formal coding skills will not be taught, although specific questions will be answered. Students must use the relevant on-line manuals and tutorials to acquire specific coding knowledge.

Solid attempts to answer the questions will generally receive at least 50%
Good attempts will generally receive up to 75%
Some degree of originality and flair will generally be required to achieve above 75%

Final Exam

Type: Exam - during Exam Period (Central)
Learning Objectives Assessed: 2, 3, 5
Due Date:
Examination Period
Weight: 30%
Perusal: 10 minutes
Duration: 120 minutes
Format: Multiple-choice, Short answer, Problem solving
Task Description: Mix of muti choice questions, problems, and short answers
Criteria & Marking: Mark based on number of correct answers to multiple choice questions.

6. Policies & Guidelines

This section contains the details of and links to the most relevant policies and course guidelines. For further details on University Policies please visit myAdvisor and the University Handbook of Policies and Procedures.

6.1 Assessment Related Policies and Guidelines

University Policies & Guidelines

An overview of the University’s assessment-related policies can be found on myAdvisor (http://www.uq.edu.au/myadvisor/index.html?page=2910).

Academic Integrity
It is the University's task to encourage ethical scholarship and to inform students and staff about the institutional standards of academic behaviour expected of them in learning, teaching and research. Students have a responsibility to maintain the highest standards of academic integrity in their work. Students must not cheat in examinations or other forms of assessment and must ensure they do not plagiarise.

Plagiarism
The University has adopted the following definition of plagiarism:

Plagiarism is the act of misrepresenting as one's own original work the ideas, interpretations, words or creative works of another. These include published and unpublished documents, designs, music, sounds, images, photographs, computer codes and ideas gained through working in a group. These ideas, interpretations, words or works may be found in print and/or electronic media.

Students are encouraged to read the UQ Academic Integrity and Plagiarism policy (http://www.uq.edu.au/hupp/index.html?page=25128) which makes a comprehensive statement about the University's approach to plagiarism, including the approved use of plagiarism detection software, the consequences of plagiarism and the principles associated with preventing plagiarism.

Feedback on Assessment
Feedback is essential to effective learning and students can expect to receive appropriate and timely feedback on all assessment. For a detailed explanation of the feedback you are entitled to, you should consult the policy on Student Access to Feedback on Assessment. (http://www.uq.edu.au/hupp/index.html?page=25114&pid=25075)

As a student you have a responsibility to incorporate feedback into your learning; make use of the assessment criteria that you are given; be aware of the rules, policies and other documents related to assessment; and provide teachers with feedback on their assessment practices.

There are certain steps you can take if you feel your result does not reflect your performance. Please refer to the myAdvisor web site. (http://www.uq.edu.au/myadvisor/index.html?page=2953&pid=2910)

Feedback in this Course

A TEDI survey will be run near the end of the course. Feel free to email me or the course newsgroup at any time.

School of Information Technology and Electrical Engineering Assessment Guidelines

Misconduct

Further to the statement on academic integrity and plagiarism above, students are required to read and understand the ITEE policy on Student Misconduct (http://www.itee.uq.edu.au/about_ITEE/policies/student-misconduct.html).

Late Arrival or Non-attendance at Examinations

The policy and procedure for late arrival or non-attendance at centrally controlled examinations is set out in the University's Examinations policy (HUPP 3.30.5), sections 8 and 10.2.

The way in which late arrival at a School-controlled examination is dealt with will be at the discretion of the course coordinator, who may be guided by the policy for centrally controlled exams.

In the case that a student requests a special exam for a School-controlled exam, the request will be considered and, if allowed, the timing shall be determined by the course coordinator, in consultation with the School's Chief Examiner where necessary, and in accordance with HUPP 3.30.5. Unless otherwise indicated in the Course Profile, applications must be made in writing to the Head of School no later than one week after the exam. Late applications will not be accepted.

Examination Feedback

In addition to the advice above, students wishing to view examination answer scripts and/or question papers should consult with the School office (Room 217, General Purpose South Building [78], St Lucia; Room 218, Building 1, Ipswich) regarding arrangements. The ITEE policy on exam script viewing is available at http://study.itee.uq.edu.au/current_students/exam_script_viewing.html.

Supplementary Assessment

If you fail this course you may be eligible for supplementary assessment - see the general award rules and/or your program rules for details. You should note that even though you may be eligible for supplementary assessment under these rules, in some circumstances there may be no practical assessment that can be offered to allow you to meet the minimum passing requirements. These circumstances may include failure based on:

group or team based assessment;
attendance or class participation requirements;
laboratory-based assessment, where laboratories can't practically be made available after classes have finished;
project or thesis-based assessment, where a significant period of time would be required to undertake supplementary assessment;
progressive assessment, where subsequent assessment items build on earlier assessment items; or
multiple assessment items, where it is impractical to offer multiple supplementary assessment items.

If the course coordinator determines that there is no practical supplementary assessment that can be offered to allow you to improve your grade, then you will not be offered supplementary assessment and your grade will remain unchanged.

6.2 Other Policies and Guidelines

University Policies and Guidelines

Placement Courses
Students on a placement course – also known as a work placement, internship, industry study, industry experience, clinical practice, clinical placement, practical work, practicum, fieldwork, teaching practice – should refer to the University policy, Placement Courses (http://www.uq.edu.au/hupp/index.html?page=25120&pid=25075) for detailed information.

Working with Children
Students whose studies include a professional/work placement, internship, clinical practice, teaching practice or other similar activity which involves them in regular contact with children should refer to the University policy, Working with Children Check - "blue card" (http://www.uq.edu.au/hupp/index.html?page=25004&pid=24963) to find out how to apply for a ‘blue card’.

Students with a Disability
Any student with a disability who may require alternative academic arrangements, including assessment, in the course/program is encouraged to seek advice at the commencement of the semester from a Disability Adviser at Student Support Services. Refer to the University policy, Students with a Disability (Disability Action Plan) (http://www.uq.edu.au/hupp/index.html?page=25122&pid=25075) and to the policy on Special Arrangements for Examinations for Students with a Disability (http://www.uq.edu.au/hupp/index.html?page=25111&pid=25075

Where an adjustment is made to an accredited program, it is the responsibility of the relevant Faculty to liaise with professional and registration bodies regarding the acceptability of the change/s.

Occupational Health and Safety
Undergraduate Students (http://www.uq.edu.au/hupp/index.html?page=25055&pid=25015) and Postgraduate Students (http://www.uq.edu.au/hupp/index.html?page=25057&pid=25015) should be familiar with the University policies on occupational health and safety in the laboratory.

Other School of Information Technology and Electrical Engineering Guidelines

Ethical Clearance

If your course involves assignment or project work involving human subjects or human-related materials, you must investigate the need for ethical clearance and obtain it when required. Information on ethical clearance can be found at http://www.uq.edu.au/research/orps/index.html?page=5064&pid=5256.

Other Course Guidelines

None

Learning Summary

Below is a table showing the relationship between the learning objectives for this course and the broader graduate attributes developed, the learning activities used to develop each objective and the assessment task used to assess each objective.

Learning Objectives

After successfully completing this course you should be able to:

1  Demonstrate practical skills in implementing real-time image processing systems in Matlab
2  Apply their theoretical framework to understand new developments DSP and image processing operations
3  Apply their problem solving skills in signal and image processing through an emphasis on practical usage, rather than mere discussion of algorithms
4  Demonstrate solid understanding of the theory through coding and implementation of DSP algorithms in MATLAB
5  Demonstrate an international perspective on the field through the advanced topics delivered by guest lecturers and recognized researchers

Assessment & Learning Activities

	Learning Objectives
	1	2	3	4	5
Learning Activities
Lecture Series (Lecture Series)
Tutorial/Practical in Computer Laboratory (Tutorial)
Assessment Tasks
Biometric Security
Assignment 1
Assignment 2
Assignment 3
Assignment 4
Assignment 5
Final Exam

Graduate Attributes

Successfully completing this course will contribute to the recognition of your attainment of the following UQ (Postgrad Coursework) graduate attributes:

	Learning Objectives
	1	2	3	4	5
Graduate Attributes
*A IN-DEPTH KNOWLEDGE OF THE FIELD OF STUDY*
A2. A broad understanding of the field of study, including how other disciplines relate to the field of study.
A3. A comprehensive and in-depth knowledge in the field of study.
A5. An international perspective on the field of study.
A7. An appreciation of the link between theory and practice.
*B EFFECTIVE COMMUNICATION*
B1. The ability to collect, analyse and organise information and ideas and to convey those ideas clearly and fluently, in both written and spoken forms.
B2. The ability to interact effectively with others in order to work towards a common outcome.
B3. The ability to select and use the appropriate level, style and means of communication.
B4. The ability to engage effectively and appropriately with information and communication technologies.
B5. The ability to practise as part of an interdisciplinary team.
*C INDEPENDENCE AND CREATIVITY*
C2. The ability to work and learn independently and effectively.
C3. The ability to generate ideas and adapt innovatively to changing environments.
C5. The ability to formulate and investigate problems, create solutions, innovate and improve current practices.
C6. The abilities and skills that provide a foundation for future leadership roles.
*D CRITICAL JUDGEMENT*
D2. The ability to apply critical reasoning to issues through independent thought and informed judgement.
D4. The ability to process material and to critically analyse and integrate information from a wide range of sources.
D5. The ability to evaluate opinions, make decisions and to reflect critically on the justifications for decisions using an evidence-based approach.
*E ETHICAL AND SOCIAL UNDERSTANDING*
E1. An understanding of social and civic responsibility.
E3. An appreciation of the philosophical and social contexts of a discipline.
E4. A knowledge and respect of ethics and ethical standards in relation to a major area of study.
E5. A knowledge of other cultures and times and an appreciation of cultural diversity.
E7. The ability to work effectively and sensitively across all areas of society.
E8. An understanding of and respect for the roles and expertise of associated disciplines.

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ELEC7602 - Sem 1 2008 - St Lucia - Internal

1. General Course Information

1.1 Course Details

1.2 Course Introduction

1.3 Course Staff

1.4 Timetable

2. Aims, Objectives & Graduate Attributes

2.1 Course Aims

2.2 Learning Objectives

2.3. Graduate Attributes

3. Learning Resources

3.1 Required Resources

3.2 Recommended Resources

3.3 University Learning Resources

3.4 School of Information Technology and Electrical Engineering Learning Resources

3.5 Other Learning Resources & Information

4. Teaching & Learning Activities

4.1 Learning Activities

4.2 Other Teaching and Learning Activities Information