Hybrid method based on topography for robust detection of iris center and eye corners

Date

2013

Director

Publisher

ACM (Association for Computing Machinery)
Acceso abierto / Sarbide irekia
Artículo / Artikulua
Versión aceptada / Onetsi den bertsioa

Project identifier

  • MICINN//TIN2009-12247/ES/ recolecta
Impacto
No disponible en Scopus

Abstract

A multi-stage procedure to detect eye features is presented. Multiresolution and topographic classification are used to detect the iris center. The eye corner is calculated combining valley detection and eyelid curve extraction. The algorithm is tested in the BioID database and in a proprietary database containing more than 1200 images. The results show that the suggested algorithm is robust and accurate. Regarding the iris center our method obtains the best average behavior for the BioID database compared to other available algorithms. Additional contributions are that our algorithm functions in real time and does not require complex post processing stages.

Description

Keywords

Computing methodologies, Artificial intelligence, Computer vision, Computer visions tasks, Human-centered computing, Human-computer interaction (HCI), Interaction devices, Touch screens

Department

Ingeniería Eléctrica, Electrónica y de Comunicación / Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren

Faculty/School

Degree

Doctorate program

item.page.cita

item.page.rights

© 2010 ACM. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Arantxa Villanueva, Victoria Ponz, Laura Sesma-Sanchez, Mikel Ariz, Sonia Porta, and Rafael Cabeza. 2013. Hybrid method based on topography for robust detection of iris center and eye corners. ACM Trans. Multimedia Comput. Commun. Appl. 9, 4, Article 25 (August 2013), 20 pages. DOI: https://doi.org/10.1145/2501643.2501647

Licencia

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