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EEE8010 : Advanced Multimedia Systems (Inactive)

  • Inactive for Year: 2022/23
  • Module Leader(s): Professor Satnam Dlay
  • Lecturer: Dr Mohsen Naqvi
  • Owning School: Engineering
  • Teaching Location: Newcastle City Campus
Semester 2 Credit Value: 15
ECTS Credits: 8.0


To introduce students to the fundamentals of image processing and provide them with essential knowledge about the main themes, so that, in the future, the students will be able to readily apply their knowledge in industry or research or further enhance it by self study.

Outline Of Syllabus

1. Image Processing and Computer Vision Background, Image Processing and Computer Vision Applications Digital Image Processing Hierarchy.
2. Human Perception of Pictures, Digital Image Processing Hardware.
3. Image Model, Amplitude digitisation.
4. Intensity Quantisation, Spatial co-ordinate digitisation.
5. Image Sampling, Image Quality, Image Pixel Relationships, Linear Operators, 2-D Transforms.
6. Spatial Domain Methods, Frequency Domain Methods.
7. Inverse Filtering.
8. Image Compression, Redundancy Types, Lossless and Lossy Compression, Image Compression Standard.
9. Object Detection Methods, Edge Liking and Boundary Detection, Thresholding Methods, Region Orientated Methods.
10. Object Representation and Description, Representation schemes, Description.
11. Pattern Recognition, Decision Theoretic Methods for Recognition.

Advance material drawn from: Video coding standards such as MPEG video Standaerd verification models and H263+ video coding at low bit rates.

Case Study Lectures.

MATLAB Image Processing Toolbox.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture361:0036:00N/A
Guided Independent StudyAssessment preparation and completion12:202:20Final exam
Guided Independent StudyAssessment preparation and completion360:3018:00Revision for final examination
Guided Independent StudyAssessment preparation and completion10:400:40In-course assessment
Guided Independent StudyAssessment preparation and completion180:154:30Revision for in-course assessment
Guided Independent StudyDirected research and reading52:0010:00Reading of recommended literature and textbooks
Guided Independent StudyIndependent study178:3078:30Reviewing lecture notes; general reading
Jointly Taught With
Code Title
EEE3013Image Processing and Machine Vision
EEE8028Image Processing and Machine Vision
Teaching Rationale And Relationship

Lectures provide core material and guidance for further reading, problem solving practice is integrated into lecture structure.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Description Length Semester When Set Percentage Comment
Written Examination1402A80Candidates must answer one long question from section A (choice of two) and two long questions from section B (choice of 3)
Written Examination402A20Candidates must answer 20 multiple choice questions
Exam Pairings
Module Code Module Title Semester Comment
EEE3013Image Processing and Machine Vision2N/A
Assessment Rationale And Relationship

The examination provides the opportunity for the student to demonstrate their understanding of the course material and their ability to apply critical thinking. The problem solving aspects of the assessment enable student to demonstrate that they are able to apply this understanding and their analysis and synthesis skills to novel situations. There is an in-course assessment using multiple choice questions to allow feedback early on in the course.

Reading Lists