CSC5029Z - Introduction To Image Processing And Computer

12 credits at NQF level 9

Entry Requirements:

Admission into the Master's degree specialising in Computer Science, or permission from the course convener. Experience in modelling (ER, UML Class diagrams) and some familiarity with logic will be helpful.

Course Outline:

To introduce students to basic concepts in computer vision and image processing, oriented towards solving real world, practical image analysis problems. The student will be introduced to basic concepts from digital signal processing, and a foundation built that will allow understanding of how more sophisticated schemes such as image analysis/segmentation which can be used to describe image and volumetric data at a higher, more useful, levels of abstraction. Case studies and papers will be examined which relate this to real-world problems. A number of lectures (as indicated below) will be presented by the course convener, interspersed with paper/review sessions in which topical papers are discussed and followed up by review questions. Topic will include: Basic Signal processing; Image Transforms & Operations; Feature Detection; Object Descriptions; Basic Segmentation & Registration; Fundamental Segmentation techniques; Machine Learning & GAs in Cvision; Case Study; and Paper Reviews.