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Physical Analogies for Ear Recognition

Physical Analogies for Ear Recognition
Physical Analogies for Ear Recognition
Hurley et al [1,2,3] have developed a pair of invertible linear transforms called the force field transform and potential energy transform which transforms an ear image into a force field by pretending that pixels have a mutual attraction proportional to their intensities and inversely to the square of the distance between them rather like Newton's Law of Universal Gravitation. Underlying this force field there is an associated potential energy field which in the case of an ear takes the form of a smooth surface with a number of peaks joined by ridges. The peaks correspond to potential energy wells and to extend the analogy the ridges correspond to potential energy channels. Since the transform also turns out to be invertible, all of the original information is preserved and since the otherwise smooth surface is modulated by these peaks and ridges, it is argued that much of the information is transferred to these features and that therefore they should make good features. An analysis of the mechanism of this algorithmic field line feature extraction approach leads to a more powerful method called convergence feature extraction based on the divergence of force direction revealing even more information in the form of anti-wells and anti-channels.
1082-1088
Springer
Hurley, David
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Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Hurley, David
d0abd3e5-ffac-4160-bb00-042083251d79
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12

Hurley, David and Nixon, Mark (2009) Physical Analogies for Ear Recognition. In, Encyclopedia of Biometrics. Springer, pp. 1082-1088.

Record type: Book Section

Abstract

Hurley et al [1,2,3] have developed a pair of invertible linear transforms called the force field transform and potential energy transform which transforms an ear image into a force field by pretending that pixels have a mutual attraction proportional to their intensities and inversely to the square of the distance between them rather like Newton's Law of Universal Gravitation. Underlying this force field there is an associated potential energy field which in the case of an ear takes the form of a smooth surface with a number of peaks joined by ridges. The peaks correspond to potential energy wells and to extend the analogy the ridges correspond to potential energy channels. Since the transform also turns out to be invertible, all of the original information is preserved and since the otherwise smooth surface is modulated by these peaks and ridges, it is argued that much of the information is transferred to these features and that therefore they should make good features. An analysis of the mechanism of this algorithmic field line feature extraction approach leads to a more powerful method called convergence feature extraction based on the divergence of force direction revealing even more information in the form of anti-wells and anti-channels.

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Published date: 2009
Additional Information: Chapter: Physi
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 268239
URI: https://eprints.soton.ac.uk/id/eprint/268239
PURE UUID: 64e42831-5b71-482f-87ff-ff1845b7d3b1
ORCID for Mark Nixon: ORCID iD orcid.org/0000-0002-9174-5934

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Date deposited: 19 Nov 2009 16:58
Last modified: 17 Jul 2018 00:36

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