Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/46131
Título: A decision-level fusion strategy for multimodal ocular biometric in visible spectrum based on posterior probability
Autores/as: Das, Abhijit
Pal, Umapada
Ferrer, Miguel A. 
Blumenstein, Michael
Clasificación UNESCO: 3307 Tecnología electrónica
Palabras clave: Iris recognition
Image color analysis
Feature extraction
Support vector machines
Probability, et al.
Fecha de publicación: 2018
Publicación seriada: IEEE International Joint Conference on Biometrics, IJCB 2017
Conferencia: 2017 IEEE International Joint Conference on Biometrics, IJCB 2017 
Resumen: 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.
URI: http://hdl.handle.net/10553/46131
ISBN: 9781538611241
DOI: 10.1109/BTAS.2017.8272772
Fuente: IEEE International Joint Conference on Biometrics, IJCB 2017,v. 2018-January, p. 794-798
Colección:Actas de congresos
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