The image ray transform for structural feature detection
The image ray transform for structural feature detection
The use of analogies to physical phenomena is an exciting paradigm in computer vision that allows unorthodox approaches to feature extraction, creating new techniques with unique properties. A technique known as the "image ray transform" has been developed based upon an analogy to the propagation of light as rays. The transform analogises an image to a set of glass blocks with refractive index linked to pixel properties and then casts a large number of rays through the image. The course of these rays is accumulated into an output image. The technique can successfully extract tubular and circular features and we show successful circle detection, ear biometrics and retinal vessel extraction. The transform has also been extended through the use of multiple rays arranged as a beam to increase robustness to noise, and we show quantitative results for fully automatic ear recognition, achieving 95.2% rank one recognition across 63 subjects.
vision, feature extraction, circle detection, biometrics, medical imaging
2053-2060
Cummings, Alastair H.
2a7f965a-a8fd-4c1c-afc8-38128765ed6f
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Carter, John N.
e05be2f9-991d-4476-bb50-ae91606389da
1 November 2011
Cummings, Alastair H.
2a7f965a-a8fd-4c1c-afc8-38128765ed6f
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Carter, John N.
e05be2f9-991d-4476-bb50-ae91606389da
Cummings, Alastair H., Nixon, Mark S. and Carter, John N.
(2011)
The image ray transform for structural feature detection.
Pattern Recognition Letters, 32 (15), .
(doi:10.1016/j.patrec.2011.08.020).
Abstract
The use of analogies to physical phenomena is an exciting paradigm in computer vision that allows unorthodox approaches to feature extraction, creating new techniques with unique properties. A technique known as the "image ray transform" has been developed based upon an analogy to the propagation of light as rays. The transform analogises an image to a set of glass blocks with refractive index linked to pixel properties and then casts a large number of rays through the image. The course of these rays is accumulated into an output image. The technique can successfully extract tubular and circular features and we show successful circle detection, ear biometrics and retinal vessel extraction. The transform has also been extended through the use of multiple rays arranged as a beam to increase robustness to noise, and we show quantitative results for fully automatic ear recognition, achieving 95.2% rank one recognition across 63 subjects.
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e-pub ahead of print date: 10 September 2011
Published date: 1 November 2011
Keywords:
vision, feature extraction, circle detection, biometrics, medical imaging
Organisations:
Vision, Learning and Control
Identifiers
Local EPrints ID: 272778
URI: http://eprints.soton.ac.uk/id/eprint/272778
PURE UUID: 136f260b-1c64-4090-9748-5d7085dd12d4
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Date deposited: 16 Sep 2011 09:57
Last modified: 15 Mar 2024 02:35
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Author:
Alastair H. Cummings
Author:
John N. Carter
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