EEE3013 : Image Processing and Machine Vision
- Offered for Year: 2022/23
- Module Leader(s): Professor Satnam Dlay
- Owning School: Engineering
- Teaching Location: Newcastle City Campus
Semesters
| Semester 2 Credit Value: | 10 |
| ECTS Credits: | 5.0 |
Aims
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. The Course is divided into two sections: Image Processing and Machine Vision.
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 coordinate digitisation: Image Sampling, Image Quality, Image Pixel Relationships.
Linear Operators, 2-D Transforms. Spatial Domain Methods (filters), Frequency Domain Methods. Inverse Filtering.
Image. Compression, Redundancy Types, Lossless and Lossy Compression, Image Compression
Standards.
Object Detection Methods, Edge Liking and Boundary Detection
Thresholding Methods, Region Oriented Methods. Matrix manipulation; Hotelling algorithm, Karhunen–Loève compression
Object Representation and Description, Representation schemes,
Description. Pattern Recognition, Decision Theoretic Methods for Recognition.
Case Study Lectures.
Use of Software such as MATLAB/Python to demonstrate Image processing and Machine Vision Techniques.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Scheduled Learning And Teaching Activities | Lecture | 11 | 2:00 | 22:00 | 2x1hr lectures per week over 11 weeks. |
| Structured Guided Learning | Lecture materials | 5 | 0:30 | 2:30 | One online synchronous tutorial every other week from second week, covering tutorial sheets. |
| Guided Independent Study | Assessment preparation and completion | 1 | 2:00 | 2:00 | Final Exam in Assessment Period |
| Guided Independent Study | Assessment preparation and completion | 12 | 1:00 | 12:00 | Revision for final exam |
| Structured Guided Learning | Structured research and reading activities | 11 | 1:00 | 11:00 | Reading activity to supplement knowledge of material taught in each week. |
| Scheduled Learning And Teaching Activities | Workshops | 5 | 1:00 | 5:00 | One online synchronous tutorial every other week from second week, covering tutorial sheets. |
| Guided Independent Study | Independent study | 1 | 45:30 | 45:30 | Reviewing lecture notes; general reading |
| Total | 100:00 |
Teaching Rationale And Relationship
Non-synchronous videos and face-to-face lectures provides the core material and synchronous review sessions give students the opportunity to query material taught in that week. Face-to-face lectures can be replaced with online synchronous sessions support by non-synchronous videos if the public health situation requires it.
Problem solving is introduced and practiced through synchronous tutorial sessions.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Exams
| Description | Length | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|---|
| Written Examination | 120 | 2 | A | 100 | Choice of 3 question from 2 from Image processing and 2 from machine vision |
Exam Pairings
| Module Code | Module Title | Semester | Comment |
|---|---|---|---|
| EEE8098 | Image Processing and Computer Vision | 2 | N/A |
Formative Assessments
| Description | Semester | When Set | Comment |
|---|---|---|---|
| Written exercise | 1 | M | Tutorial Question on Image Processing set in the middle of the semester |
Assessment Rationale And Relationship
Lectures provide the core material as well as guidance for further reading. Problem practice is integrated into lecture structure, examples are given in the use of the software tools.
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
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- EEE3013's Timetable