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(2015) Human recognition based on ear biometric data. MSc thesis.

The main obstacle hindering the deployment of ear biometrics is the potential occlusion by hair.

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Thermal imaging of ear biometrics for authentication …

[en] This master’s thesis studies the potential of ear biometrics using acoustical waves. The goal is to know whether it is possible and accurate to authenticate someone with a system using headphones and microphones on ears. The idea is to send a signal with the headphones in the ears of the subject and get the reflections with microphones. These reflections depend on the shape of the ear and therefore could be used to authenticate someone.
For this research, different handcrafted prototypes have been manufactured. By placing microphones in different headphones. Some physical expectations of the measurable data have been studied allowing to see the differences that could occur between people. Then some databases with different users have been established, a pre-processing scheme of the data has been discussed and two recognition algorithms have been implemented and tested on these databases. The different parameters for these algorithms have been studied in order to determine the best way to recognize people correctly and get optimal parameters. The results were quite satisfying and in accordance with previous studies. The efficiency depends on the headset but the best obtained EER value was equal to 98.99 %. As an additional work, the detection of the correct positioning of the headset has also been briefly studied. This detection was really good for some people while for others it was not. Finally, further work and ideas for future studies are proposed and presented.

Abstract [en] This master’s thesis studies the potential of ear biometrics using acoustical waves
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In this paper, a new method to represent human ear for biometrics purposes is introduced. Even if ear has a uniform distribution of color, human external ear characteristics are considered unique to each individual and permanent during the lifetime of an adult. For these reasons ear biometrics approaches are relying on morphological ear properties. Even if ear biometrics is a young topic a variety of approaches have been proposed to characterize the ear geometry and topology. Moreover, note that the ear morphology is the biggest human head concavity, and that its convex hull complement is mainly convex. In this connection, the matching potential for ear discrimination can be effectively exploited through an Extended Gaussian Image (EGI) representation. The original EGI representation and its correspondent concrete data-structure are here applied to ear description and discussed for human authentication and identification purposes.

Thermal imaging of ear biometrics for authentication purposes

This thesis will look at theear as a biometric feature, and how thermal images may improve the performance ofsuch authentication systems.
Photo provided by Flickr

In the field of ear biometrics, despite recent developments, there are no freely available tools or databases captured in the wild that would ease the comparison of methods for ear biometric recognition. A new ear database captured in the wild was developed as a part of this thesis as well as a new toolbox for ear recognition. Rotation invariant local phase quantization method was also applied, for the first time in the field of ear biometrics, together with a fusion of this method with vectors of normalized images. Results are comparable but not better than the state-of-the-art, however, with the fusion we have achieved better results than the rotation invariant local phase quantization alone. The developed toolbox for ear recognition presents a new step towards standardization in the field of ear recognition and tests on the ear database have shown that the database presents greater challenge than the existing ones, but it is still comparable, which makes it suitable for further use.

[en] This master’s thesis studies the potential of ear biometrics using acoustical waves. The goal is to know whether it is possible and accurate to authenticate someone with a system using headphones and microphones on ears. The idea is to send a signal with the headphones in the ears of the subject and get the reflections with microphones. These reflections depend on the shape of the ear and therefore could be used to authenticate someone.
For this research, different handcrafted prototypes have been manufactured. By placing microphones in different headphones. Some physical expectations of the measurable data have been studied allowing to see the differences that could occur between people. Then some databases with different users have been established, a pre-processing scheme of the data has been discussed and two recognition algorithms have been implemented and tested on these databases. The different parameters for these algorithms have been studied in order to determine the best way to recognize people correctly and get optimal parameters. The results were quite satisfying and in accordance with previous studies. The efficiency depends on the headset but the best obtained EER value was equal to 98.99 %. As an additional work, the detection of the correct positioning of the headset has also been briefly studied. This detection was really good for some people while for others it was not. Finally, further work and ideas for future studies are proposed and presented.

This thesis will look at the ear as a biometric feature, ..

Comparing to the-state-of-the-art technologies, our work has taken a further step in twin recognition by using biometrics.
Photo provided by Flickr

So far ear biometric approaches have mostly used general properties and overall appearance of ear images in recognition, while the structure of the ear has not been discussed.

We develop and investigate two new scorelevel combinations, i.e., holistic and nonlinear fusion, and comparatively evaluate them with more popular score-level fusion approaches to ascertain their effectiveness in the proposed system.

Key words: Fingerprint Recognization,FingerVein Recognization,Fusion,Hand Biometrics

Reference
[1] Encyclopedia of Biometrics, S.

The next logical step towards a broader application of ear biometrics is to create automatic ear recognition systems.
Photo provided by Flickr
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    Résumé [en] This master’s thesis studies the potential of ear biometrics using acoustical waves

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