Computer Science

Image technologies have advanced rapidly in recent decades. Many images and much image- based data become available in different domains, from biology to astrophysics,  industry and medicine. Such images carry useful information. This module presents some of  techniques used for analysing objects presented on images, how they are matched, recognised, identified and classified.

The main aim of this module is to introduce students to computer understanding of digital images of real objects. The module describes various image processing methods that allow computers to select and recognize particular objects, segment them into regions of interest, extract suitable features, and enable an efficient classification of the considered objects.

Module Specific Skills and Knowledge:
1 demonstrate ability to write dedicated software for the computer analysis of digital images taken from a variety of applications;
2 demonstrate an ability to apply standard methods of  feature extraction, invariants,  and shape descriptors on digital images;
3 demonstrate an ability to  develop their independent approaches to developing algorithms on image understanding.
Discipline Specific Skills and Knowledge:
4 demonstrate a good theoretical and applied knowledge on intelligence in image processing in a range of areas.
Personal and Key Transferable/ Employment Skills and  Knowledge:
5 demonstrate an ability to select and use appropriate tools for problems solving;
6 communicate effectively both in written and oral presentations.

The syllabus for the module can be structured as below: Image Processing Methods: Definition of images, resolution, image features, moments, moments invariants; Shape Analysis Methods: Boundary based shape descriptors, area based shape descriptors, computation of shape descriptors,statistical methods for describing shape, encasing objects, human perception consideration; Curves, regression; Object encoding: Chain codes, filters, histograms. Classification algorithms.

If a module is normally assessed entirely by coursework, all referred/deferred assessments will normally be by assignment.
If a module is normally assessed by examination or examination plus coursework, referred and deferred assessment will normally be by examination. For referrals, only the examination will count, a mark of 40% being awarded if the examination is passed. For deferrals, candidates will be awarded the higher of the deferred examination mark or the deferred examination mark combined with the original coursework mark.

ELE – http://vle.exeter.ac.uk

Reading list for this module: