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EEE3013 : Image Processing and Machine Vision

  • Offered for Year: 2020/21
  • Module Leader(s): Professor Satnam Dlay
  • Owning School: Engineering
  • Teaching Location: Newcastle City Campus
Semester 2 Credit Value: 10
ECTS Credits: 5.0


To introduce the students to the fundamentals of image processing and provide them with the 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

Image Processing and Computer Vision Background, Image Processing and Computer Vision Applications Digital Image Processing Hierarchy: Human Perception of Pictures, Digital Image Processing Hardware. Image Model, Amplitude digitisation: Intensity Quantisation, Spatial co-ordinate digitisation: Image Sampling, Image Quality, Image Pixel Relationships, Linear Operators, 2-D Transforms. Spatial Domain Methods, Frequency Domain Methods. Inverse Filtering. Image Compression, Redundancy Types, Lossless and Lossy Compression, Image Compression Standards. Matrix manipulation;Hotelling algorithm, Karhunen–Loève compression, Object Detection Methods, Edge Liking and Boundary Detection, Thresholding Methods, Region Oriented Methods. Object Representation and Description, Representation schemes, Description. Pattern Recognition, Decision Theoretic Methods for Recognition.

Case Study Lectures

MATLAB Iage Processing Toolbox

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion240:3012:00Revision for final examination
Guided Independent StudyAssessment preparation and completion12:002:00Final exam
Scheduled Learning And Teaching ActivitiesLecture241:0024:00N/A
Guided Independent StudyIndependent study162:0062:00Reviewing 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.

Assessment Methods

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

Description Length Semester When Set Percentage Comment
Written Examination1202A100Candidates to answer three long questions from a choice of four.
Assessment Rationale And Relationship

Lectures provide the core material as well as guidance for further reading. Problem practice is integrated into lecture structure, practice is given in the use of the Matlab image processing toolbox.

The examination provides the opportunity for the students to demonstrate their understanding of the course material and their ability to apply critical thinking. The problem solving aspects of the assessment enable the student to demonstrate that they are able to apply this understanding and their analysis and synthesis skills to novel situations.

Reading Lists