2015/16 Taught Postgraduate Module Catalogue
COMP5870M Image Analysis
15 creditsClass Size: 15
Module manager: Professor David Hogg
Email: d.c.hogg@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2015/16
This module is not approved as an Elective
Module summary
Image analysis techniques are used in many domains such as medical image analysis, navigation and visual surveillance. This module studies a selection of these techniques in depth. You will learn about the problems and solutions in particular application areas; how to evaluate the performance of the methods and to apply the theoretical knowledge gained to design image analysis systems for solving specific problemsObjectives
On completion of this module, students should be able to:- demonstrate an understanding of the principal ideas and techniques of image analysis;
- demonstrate an understanding of a selection of these techniques in depth;
- appreciate the problems and solutions adopted in some of its main application areas;
- apply the theoretical knowledge gained in the module to the design of image analysis systems for solving specific problems.
Learning outcomes
On completion of the year/programme students should have provided evidence of being able to:
-to demonstrate in-depth, specialist knowledge and mastery of techniques relevant to the discipline and/or to demonstrate a sophisticated understanding of concepts, information and techniques at the forefront of the discipline;
-to exhibit mastery in the exercise of generic and subject-specific intellectual abilities;
-to demonstrate a comprehensive understanding of techniques applicable to their own research or advanced scholarship;
-proactively to formulate ideas and hypotheses and to develop, implement and execute plans by which to evaluate these;
-critically and creatively to evaluate current issues, research and advanced scholarship in the discipline.
Skills outcomes
Computer programming.
Performance evaluation.
Syllabus
Image formation; image statistics and representations; edge and feature detection; texture; colour; stereo; frequency domain analysis; noise models and image restoration; shape representation; motion detection; multi resolution representations; segmentation; model based object recognition; image compression; applications of image analysis.
Teaching methods
Delivery type | Number | Length hours | Student hours |
Laboratory | 11 | 1.00 | 11.00 |
Lecture | 22 | 1.00 | 22.00 |
Private study hours | 117.00 | ||
Total Contact hours | 33.00 | ||
Total hours (100hr per 10 credits) | 150.00 |
Private study
Consolidation of knowledge;Additional reading;
Completion of courseworks.
Opportunities for Formative Feedback
Discussion in lectures.Performance in courseworks.
Discussion in Laboratory sessions.
Methods of assessment
Coursework
Assessment type | Notes | % of formal assessment |
Assignment | Coursework 1 | 20.00 |
Assignment | Coursework 2 | 20.00 |
Total percentage (Assessment Coursework) | 40.00 |
This module is re-assessed by exam only.
Exams
Exam type | Exam duration | % of formal assessment |
Open Book exam | 2 hr | 60.00 |
Total percentage (Assessment Exams) | 60.00 |
This module is re-assessed by exam only.
Reading list
There is no reading list for this moduleLast updated: 05/11/2015
Browse Other Catalogues
- Undergraduate module catalogue
- Taught Postgraduate module catalogue
- Undergraduate programme catalogue
- Taught Postgraduate programme catalogue
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