title: |
Bipolarity in ear biometrics |
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publication: |
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part of series: |
Advances in Intelligent Systems Research | |
| pages: | 409 - 415 | |
DOI: |
To be assigned soon (how to use a DOI) | |
author(s): |
Joachim Nielandt |
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publication date: |
July 2011 |
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keywords: |
Ear biometrics, bipolarity, identification, soft computing |
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abstract: |
Identifying people using their biometric data is a
problem that is getting increasingly more attention.
This paper investigates a method that allows the
matching of people in the context of victim identification by using their ear biometric data. A high
quality picture (taken professionally) is matched
against a set of low quality pictures (family albums).
In this paper soft computing methods are used to
model different kinds of uncertainty that arise when
manually annotating the pictures. More specifically,
we study the use of bipolar satisfaction degrees to
explicitly handle the bipolar information about the
available ear biometrics. |
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copyright: |
©
Atlantis Press. This article is distributed under the
terms of the Creative Commons Attribution License, which permits
non-commercial use, distribution and reproduction in any medium,
provided the original work is properly cited. |
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full text: |