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Details of Grant 

EPSRC Reference: EP/I030328/1
Title: Persistent topological structures in noisy images
Principal Investigator: Kurlin, Dr V
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Mathematical Sciences
Organisation: Durham, University of
Scheme: First Grant - Revised 2009
Starts: 08 August 2011 Ends: 07 August 2013 Value (£): 99,975
EPSRC Research Topic Classifications:
Algebra & Geometry Image & Vision Computing
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
Panel History:
Panel DatePanel NameOutcome
24 May 2011 Mathematics Prioritisation Panel Meeting May 2011 Announced
Summary on Grant Application Form
The proposed research is on the interface between topology and algorithms.The methods are topological coming from the recently developed theory of persistent topology.The key idea of persistent topology is identifying features of geometric objects that remain stable for a wide range of varying parameters. The research objectives are applied and involve designing novel learning algorithms to recognise topological graphs in noisy images.A natural application is identifying a text-based advanced CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) widely used on the web to prevent automatic posting to blogs.A desired learning algorithm will be parallel like the human brain analysing local persistent properties of pixels in a noisy image.Hence it is the next step towards reverse-engineering the human brain.Other potential applications include recognising handwritten mail addresses and designing computer glasses reading signs of directions for blind people.
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