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

Authors:
Arantxa Villanueva;Victoria Ponz;Laura Sesma-Sanchez;Mikel Ariz;Sonia Porta;Rafael Cabeza
Affiliations:
Public University of Navarre;Public University of Navarre;Public University of Navarre;Public University of Navarre;Public University of Navarre;Public University of Navarre
Venue:
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Year:
2013

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Abstract

A multistage 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.