FIT3081 - Image processing - 2019

This unit introduces fundamental image processing techniques for the digital manipulation of 2D image data. Algorithms explored include those for edge detection, image enhancement, feature and shape extraction, segmentation and noise removal. The unit provides students an opportunity to develop theoretical understanding of these algorithms, and practical skills in implementing and applying them to real image data.

At the completion of this unit students will be able to:

1. explain the processes of image formation, acquisition, processing and analysis;
2. explain the type of algorithm required for a particular image processing task among a wide range of available methodologies;
3. develop programs for manipulating grey level and colour images using standard image processing algorithms;
4. develop and analyse software for image segmentation, image classification, image data mining, and computer vision;
5. develop algorithms to extract and analyse features in medical, document, and other images;
6. participate in a team as an image processing specialist communicating with other team members to develop image processing software.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two x 2-hour workshops
2. Additional requirements (all students):
   • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Advanced computer science