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CSC8628: Image Informatics

  • Offered for Year: 2026/27
  • Module Leader(s): Professor Boguslaw Obara
  • Lecturer: Dr Alma Cantu, Dr Tong Xin
  • Owning School: Computing
  • Teaching Location: Newcastle City Campus
Semesters

Your programme is made up of credits, the total differs on programme to programme.

Semester 1 Credit Value: 10
ECTS Credits: 5.0

Aims

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

Outline Of Syllabus

Topics will cover some or all of the following areas:

  • Background, Image Model, Spatial Coordinate Digitisation: Image Sampling, Image Quality, Image Pixel
    Relationships.
  • Linear Operators, Transforms, Spatial Domain Methods (Filters), Frequency Domain Methods.
  • Image Compression, Lossless and Lossy Compression, Image Compression Standards.
  • Object Detection Methods, Edge and Boundary Detection.
  • Segmentation.
  • Pattern Recognition.
  • Introduction to Convolutional Neural Network (CNN).
  • Case Studies.
  • Use of Python to demonstrate Image Informatics techniques. 

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent Study Assessment preparation and completion 10 1:00 10:00 Independent study on course content
Scheduled Learning And Teaching Activities Lecture 10 1:00 10:00 Lectures (in person)
Guided Independent Study Assessment preparation and completion 20 1:00 20:00 Background reading
Scheduled Learning And Teaching Activities Practical 10 2:00 20:00 Practicals (in person)
Guided Independent Study Project work 40 1 40:00

Main summative assignment
Total 100:00        
Teaching Rationale And Relationship

Lectures explain the underlying principles for the module and technologies that support image processing.

Lectures are complemented by supervised practical sessions to guide the application of these principles using suitable tools.

The practical work builds up experience working with a computational toolset that is used to complete a substantive project working with data from a real-world context.

Assessment Methods

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

Other Assessment
Component Semester When Set Percentage Comment
Report 1 M 100 Extended technical project. Word count; up to 1500 words, to include detailed figures demonstrating results.
Zero Weighted Pass/Fail Assessments
Description When set Comment
Oral Examination M Structured discussion inc. a software demonstration and reflection on the key learning objectives of the project work-up to 15 minutes.
Assessment Rationale And Relationship

The report tests the students’ ability to apply image processing techniques, using effective tools and methods to solve a real-world challenge.

Reading Lists

Timetable