EEE8098 : Image Processing and Computer Vision
- Offered for Year: 2019/20
- Module Leader(s): Professor Satnam Dlay
- Owning School: Engineering
- Teaching Location: Newcastle City Campus
|Semester 2 Credit Value:||20|
To introduce students to the fundamentals of multimedia systems & image processing and to provide them with essential knowledge about the main themes, so that, in the future, 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. Boundary Representation and Description, Representation schemes, Description.
11. Pattern Recognition, Decision Theoretic Methods for Recognition.
Advance material drawn from:
12. Image Compression & Coding redundancy
13. Image Compression Models - JPEG
14. H.261& H.263 video coding standards at low bit rates
15. MPEG video standards
16. Case Study Lectures.
MATLAB Image Processing Toolbox.
|Guided Independent Study||Assessment preparation and completion||40||0:30||20:00||Revision for final examination|
|Guided Independent Study||Assessment preparation and completion||1||3:00||3:00||Final exam|
|Scheduled Learning And Teaching Activities||Lecture||40||1:00||40:00||N/A|
|Guided Independent Study||Directed research and reading||10||2:30||25:00||Reading of recommended literature and textbooks|
|Guided Independent Study||Independent study||1||112:00||112:00||Reviewing lecture notes; general reading|
Teaching Rationale And Relationship
Lectures provide core material and guidance for further reading, problem solving practice is integrated into lecture structure. Self-directed learning is through self-study and group presentations.
The format of resits will be determined by the Board of Examiners
|Written Examination||180||2||A||100||End of Semester Exam|
|Module Code||Module Title||Semester||Comment|
|EEE3013||Image Processing and Machine Vision||1||N/A|
|EEE8028||Image Processing and Machine Vision||1||N/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 students 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 through group presentations on a multimedia theme.