PhD in Computer Science: Development of New, Automated Methods in Image Processing for Photogrammetry RTI (Reflectance Transformation Imaging)
University of Exeter - Computer Science
|Funding for:||UK Students, EU Students|
|Funding amount:||Not specified|
|Placed on:||16th September 2016|
|Closes:||30th October 2016|
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Primary supervisor: Dr Jacqueline Christmas
Secondary supervisor: Dr Judith Bannerman
Location: Streatham campus, Exeter
RTI is an image processing technique that combines multiple digital photographs of an object, lit from different directions, into a representation that allows the user to explore the shape and colour of its surface interactively. Mathematical techniques are used to enhance key features and to build a three-dimensional representation of the object that captures surface detail not visible to the naked eye.
This project aims to enhance and expand existing photogrammetry RTI methods by developing and implementing new, automated image processing techniques, with a particular emphasis on machine learning and artificial intelligence approaches.
The immediate application is to desk-top scale cultural heritage items, but it is anticipated that the project will broaden from desk-top imaging to imaging both in the field and through microscopes. The ultimate aim is to deliver a low-cost system, based on off-the-shelf components that can be used by non-technical operators.
You will join a growing machine learning group at Exeter, working directly with Dr Jacqueline Christmas and Dr Judith Bannerman, and we will be collaborating with Prof George Bevan of Queen’s University, Canada, who is an expert in the use of these computational photographic techniques and has a particular interest in enhancing inscriptions on weathered surfaces.
Please be advised that a significant part of the role will involve the use of flash photography.
This post is to start on 9th January 2017.
For informal enquiries about the project, please contact Dr Jacqueline Christmas, J.T.Christmas@exeter.ac.uk.
Academic entry requirements:
Applicants should have or expect to achieve at least a 2:1 Honours degree, or equivalent, in Computer Science or a closely related subject. They should have strong programming skills, an aptitude for mathematics, and an enthusiasm for research into image processing and machine learning.
Residency entry requirements:
This studentship is available to UK and EU students. International students can apply and pay the difference in tuition fees.
Location of Job:
University of Exeter, Streatham campus, Exeter
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South West England