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ShareOct. 11, 2010 — Scientists working on biometrics at the University of Southampton have found a way to identify ears with a success rate of almost 100 percent.
In a paper entitled A Novel Ray Analogy for Enrolment of Ear Biometrics just presented at the IEEE Fourth International Conference on Biometrics: Theory, Applications and Systems, scientists from the University's School of Electronics and Computer Science (ECS) described how a technique called image ray transform can highlight tubular structures such as ears, making it possible to identify them.
The research which was carried out by Professor Mark Nixon, Dr John Carter and Alastair Cummings at ECS, describes how the transform is capable of highlighting tubular structures such as
- the helix of the ear and spectacle frames and, by exploiting the
- elliptical shape of the helix, can be used as the basis of a method
- for enrolment for ear biometrics.
Professor Nixon, one of the UK's earliest researchers in this field, first proved that ears were a viable biometric back in 1999.
At that point he said that ears have certain advantages over the more established biometrics as they have a rich and stable structure that is preserved from birth to old age and instead of aging they just get bigger. The ear also does not suffer from changes in facial expression and it is firmly fixed in the middle of the side of the head against a predictable background, unlike face recognition which usually requires the face to be captured against a controlled background.
However, the fact that ears can be concealed by hair, led Professor Nixon and his team to research their use as a biometric further and to come up with new algorithms to make it possible to identify and isolate the ear from the head.
The technique presented by the scientists achieves 99.6% success at enrolment across 252 images of the XM2VTS database, displaying a resistance to confusion with hair and spectacles. These results show great potential for enhancing the detection of structural features.
"Feature recognition is one of the biggest challenges of computer vision," said Alastair Cummings, the PhD student for the research. "The ray transform technique may also be appropriate for use in gait biometrics, as legs act as tubular features that the transform is adept at extracting. The transform could also be extended to work upon 3D images, both spatial and spatio-temporal, for 3D biometrics or object tracking. It is a general pre-processing technique for feature extraction in computer images, a technology which is now pervading manufacturing, surveillance and medical applications."
A copy of at: A Novel Ray Analogy for Enrolment of Ear Biometrics can be accessed at: http://eprints.ecs.soton.ac.uk/21546/
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