View source for Publications:Periocular Recognition by Detection of Local Symmetry Patterns

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{{PublicationSetupTemplate|Author=Anna Mikaelyan, Fernando Alonso-Fernandez, Josef Bigun
|PID=757572
|Name=Mikaelyan, Anna (annmik) (Högskolan i Halmstad (2804), Akademin för informationsteknologi (16904), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), CAISR Centrum för tillämpade intelligenta system (IS-lab) (13650));Alonso-Fernandez, Fernando (feralo) (0000-0002-1400-346X) (Högskolan i Halmstad (2804), Akademin för informationsteknologi (16904), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), CAISR Centrum för tillämpade intelligenta system (IS-lab) (13650));Bigun, Josef (josef) (Högskolan i Halmstad (2804), Akademin för informationsteknologi (16904), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), CAISR Centrum för tillämpade intelligenta system (IS-lab) (13650))
|Title=Periocular Recognition by Detection of Local Symmetry Patterns
|PublicationType=Conference Paper
|ContentType=Refereegranskat
|Language=eng
|Journal=
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|HostPublication=Proceedings : Tenth International Conference on Signal-Image Technology and Internet-Based System: 23–27 November 2014: Marrakech, Morocco
|Conference=Workshop on Insight on Eye Biometrics (IEB) in conjunction with The 10th International Conference on Signal Image Technology & Internet Based Systems (SITIS), Marrakech, Morocco, 23-27 November, 2014
|StartPage=584
|EndPage=591
|Year=2014
|Edition=
|Pages=
|City=Los Alamitos, CA
|Publisher=IEEE Computer Society
|Series=
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|ISBN=978-1-4799-7978-3
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|DOI=http://dx.doi.org/10.1109/SITIS.2014.105
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|NBN=urn:nbn:se:hh:diva-26871
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|Keywords=biometrics;periocular recognition;eye;symmetry filters;structure tensor
|Categories=Signalbehandling (20205)
|ResearchSubjects=
|Projects=BBfor2
|Notes=<p>Author A. M. thanks the EU BBfor2 project for funding her doctoral research. Author F. A.-F. thanks the Swedish Research Council and the EU for for funding his postdoctoral research. Authors acknowledge the CAISR program of the Swedish Knowledge Foundation and the EU COST Action IC1106.</p>
|Abstract=<p>We present a new system for biometric recognition using periocular images. The feature extraction method employed describes neighborhoods around keypoints by projection onto harmonic functions which estimates the presence of a series of various symmetric curve families around such keypoints. The iso-curves of such functions are highly symmetric w.r.t. the keypoints and the estimated coefficients have well defined geometric interpretations. The descriptors used are referred to as Symmetry Assessment by Feature Expansion (SAFE). Extraction is done across a set of discrete points of the image, uniformly distributed in a rectangular-shaped grid positioned in the eye center. Experiments are done with two databases of iris data, one acquired with a close-up iris camera, and another in visible light with a webcam. The two databases have been annotated manually, meaning that the radius and center of the pupil and sclera circles are available, which are used as input for the experiments. Results show that this new system has a performance comparable with other periocular recognition approaches. We particularly carry out comparative experiments with another periocular system based on Gabor features extracted from the same set of grid points, with the fusion of the two systems resulting in an improved performance. We also evaluate an iris texture matcher, providing fusion results with the periocular systems as well.</p>
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|CreatedDate=2014-10-22
|PublicationDate=2014-10-22
|LastUpdated=2015-09-29
|diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:757572}}
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