A decision-level fusion strategy for multimodal ocular biometric in visible spectrum based on posterior probability

Das, A; Pal, U; Ferrer, MA; Blumenstein, M

A decision-level fusion strategy for multimodal ocular biometric in visible spectrum based on posterior probability

Das, A Pal, U Ferrer, MA Blumenstein, M

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Publication Type:: Conference Proceeding
Citation:: IEEE International Joint Conference on Biometrics, IJCB 2017, 2018, 2018-January pp. 794 - 798
Issue Date:: 2018-01-29

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Field	Value	Language
dc.contributor.author	Das, A	en_US
dc.contributor.author	Pal, U	en_US
dc.contributor.author	Ferrer, MA	en_US
dc.contributor.author	Blumenstein, M https://orcid.org/0000-0002-9908-3744	en_US
dc.date.available	2020-05-25T19:11:43Z
dc.date.issued	2018-01-29	en_US
dc.identifier.citation	IEEE International Joint Conference on Biometrics, IJCB 2017, 2018, 2018-January pp. 794 - 798	en_US
dc.identifier.isbn	9781538611241	en_US
dc.identifier.uri	http://hdl.handle.net/10453/125749
dc.description.abstract	© 2017 IEEE. In this work, we propose a posterior probability-based decision-level fusion strategy for multimodal ocular biometric in the visible spectrum employing iris, sclera and peri-ocular trait. To best of our knowledge this is the first attempt to design a multimodal ocular biometrics using all three ocular traits. Employing all these traits in combination can help to increase the reliability and universality of the system. For instance in some scenarios, the sclera and iris can be highly occluded or for completely closed eyes scenario, the peri-ocular trait can be relied on for the decision. The proposed system is constituted of three independent traits and their combinations. The classification output of the trait which produces highest posterior probability is to consider as the final decision. An appreciable reliability and universal applicability of ocular trait are achieved in experiments conducted employing the proposed scheme.	en_US
dc.relation.ispartof	IEEE International Joint Conference on Biometrics, IJCB 2017	en_US
dc.relation.isbasedon	10.1109/BTAS.2017.8272772	en_US
dc.title	A decision-level fusion strategy for multimodal ocular biometric in visible spectrum based on posterior probability	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2018-January	en_US
utslib.for	0803 Computer Software	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Strength - QSI - Centre for Quantum Software and Information
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	2018-January	en_US

Abstract:

© 2017 IEEE. In this work, we propose a posterior probability-based decision-level fusion strategy for multimodal ocular biometric in the visible spectrum employing iris, sclera and peri-ocular trait. To best of our knowledge this is the first attempt to design a multimodal ocular biometrics using all three ocular traits. Employing all these traits in combination can help to increase the reliability and universality of the system. For instance in some scenarios, the sclera and iris can be highly occluded or for completely closed eyes scenario, the peri-ocular trait can be relied on for the decision. The proposed system is constituted of three independent traits and their combinations. The classification output of the trait which produces highest posterior probability is to consider as the final decision. An appreciable reliability and universal applicability of ocular trait are achieved in experiments conducted employing the proposed scheme.

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http://hdl.handle.net/10453/125749