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2018/19 Taught Postgraduate Module Catalogue

COMP5870M Image Analysis

15 creditsClass Size: 60

Module manager: Professor David Hogg
Email: d.c.hogg@leeds.ac.uk

Taught: Semester 2 View Timetable

Year running 2018/19

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 problems

Objectives

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 and representations; feature detection; texture analysis; stereo; image restoration; shape representation; object tracking; activity analysis; multi-resolution representations; segmentation; object recognition; convolutional neural networks, image compression; applications of image analysis.

Teaching methods

Delivery typeNumberLength hoursStudent hours
Laboratory111.0011.00
Lecture221.0022.00
Private study hours117.00
Total Contact hours33.00
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 typeNotes% of formal assessment
AssignmentCoursework 120.00
AssignmentCoursework 220.00
Total percentage (Assessment Coursework)40.00

This module is re-assessed by exam only.


Exams
Exam typeExam duration% of formal assessment
Open Book exam2 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 module

Last updated: 30/04/2018

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