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Transient Biometrics Nails Dataset V02

T B N D v2

About Transient Biometric Nails Dataset v2

An extended version of an experimental dataset, called transient biometrics nails dataset (TBND), was created. TBND is composed of images of the right index finger. During acquisition the subject was instructed to lay her finger over a flat white surface and a simple point-and-shoot camera was used to acquire an image without the the use of a flash. No explicit instructions with respect to force applied were given and thus our results incorporate arbitrary force differences between users and capture sessions. Acquisition was thus done in a semi-controlled environment; apart from the white background and indirect lighting, the images present variation with respect to scale, focal plane and illumination. The dataset consists of three subsets, each one compromising the same 93 subjects, but varying on acquisition date. The first subset D01 consists of images acquired on the first acquisition day. The second subset D02 is composed of images acquired one day later. The third subset D30 was acquired 1 month after the first acquisition date. Given acquisition restrictions, the acquisitions of D30 have up to two days’ tolerance. This represents a massive expansion of the originally collected dataset TBND V01

Reference and Citation policy
Citation Policy

In the case you publish material based on this dataset then in your acknowledgements, please mention the base work as a reference.

Bibtex Reference

@Article{Barros Barbosa2016,
author=”Barros Barbosa, Igor
and Theoharis, Theoharis
and Abdallah, Ali E.”,
title=”On the use of fingernail images as transient biometric identifiers”,
journal=”Machine Vision and Applications”,
year=”2016″,
volume=”27″,
number=”1″,
pages=”65–76″,
abstract=”The significant advantages that biometric recognition technologies offer are in danger of being left aside in everyday life due to concerns over the misuse of such data. The biometric data employed so far focuses on the permanence of the characteristics involved. A concept known as `the right to be forgotten’ is gaining momentum in international law and this should further hamper the adoption of permanent biometric recognition technologies. However, a multitude of common applications are short-term and, therefore, non-permanent biometric characteristics would suffice for them. In this paper we discuss `transient biometrics,’ i.e. recognition via biometric characteristics that will change in the short term and show that images of the fingernail plate can be used as a transient biometric with a useful life-span of less than 6 months. A direct approach is proposed that requires no training and a relevant evaluation dataset is made publicly available.”,
issn=”1432-1769″,
doi=”10.1007/s00138-015-0721-y”,
url=”http://dx.doi.org/10.1007/s00138-015-0721-y”
}

Download - Transient Biometrics Nail Dataset - Version 2.0






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Transient Biometrics Nails Dataset V01

T B N D

About Transient Biometric Nails Dataset

There is plenty of scope for biometric recognition systems to become more socially acceptable, in the sense that society could accept and use such systems in day-to-day scenarios. The acceptability issue remains particularly open when dealing with non-critical scenarios and collaborative subjects. For instance, individuals will not happily offer their fingerprints just to have access to their hotel room. The points raised above limits the use of biometric technologies in a multitude of noncritical situations. This is why we introduce Transient Biometrics.

With this Transient Biometrics Nails Dataset we introduce a new idea to address the acceptability issue inherent to biometric solutions. This approach, designed for collaborative individuals, instead of recording permanent data, records transient data, i.e. data that do change over time and are thus canceled by nature. Users, who know that the biometric data they offer is going to be useless for recognition purposes after a certain amount of time, are likely to be more willing to offer it, even for day-to-day applications. This approach is termed transient biometrics; the idea is to use features with a short permanence, giving a diminutive period of recognition.

The proposed dataset is composed by three different groups of data. The data are collected images of the right index finger nail.
The first group of data (D01) has been obtained by collecting images of 32 subjects.  This happened in an indoor scenario, using diffuse lighting.
The second group of data (D08), was acquired one week after D01 and is the collection of 24 subjects. Those subjects are also part of D01.
The third and last group of data (D70) was collected 2 months after D01. It contains 17 finger nail images of subjects common to D01 and D07.

Reference and Citation policy
Citation Policy

In the case you publish material based on this dataset then in your acknowledgements, please mention the base work as a reference.

WYSIWYG Reference

Barbosa, I.B.; Theoharis, T.; Schellewald, C.; Athwal, C., “Transient biometrics using finger nails,” Biometrics: Theory, Applications and Systems (BTAS), 2013 IEEE Sixth International Conference on , vol., no., pp.1,6, Sept. 29 2013-Oct. 2 2013
doi: 10.1109/BTAS.2013.6712730
keywords: {fingerprint identification;biometric recognition systems;eye retina;finger nails;noncritical applications;research community;transient biometric characteristics;Bioinformatics;Biometrics (access control);Feature extraction;Image segmentation;Nails;Training;Transient analysis},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6712730&isnumber=6712682

Bibtex Reference

@INPROCEEDINGS{Barbosa13,
author={Barbosa, I.B. and Theoharis, T. and Schellewald, C. and Athwal, C.},
booktitle={Biometrics: Theory, Applications and Systems (BTAS), 2013 IEEE Sixth International Conference on},
title={Transient biometrics using finger nails},
year={2013},
month={Sept},
pages={1-6},
keywords={fingerprint identification;biometric recognition systems;eye retina;finger nails;noncritical applications;research community;transient biometric characteristics;Bioinformatics;Biometrics (access control);Feature extraction;Image segmentation;Nails;Training;Transient analysis},
doi={10.1109/BTAS.2013.6712730},}

Transient biometrics using finger nails

Download - Transient Biometrics Nail Dataset - Version 1.0






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