AB081. Multi-unit ocular biometric system based on corneal shapes
Cornea and Anterior segment

AB081. Multi-unit ocular biometric system based on corneal shapes

Nassima Kihal1, Isabelle Brunette2,3, Jean Meunier1

1Département d’informatique et recherche, Université de Montréal, Montreal, QC, Canada; 2Centre Universitaire d'Ophtalmologie de l'Université de Montréal et Centre de Recherche de l'Hôpital Maisonneuve-Rosemont, CIUSSS-E, Montréal, Canada; 3Hôpital Maisonneuve-Rosemont Research Center, CIUSSS-E, Montréal, Canada

Background: Our goal is to build a multi-unit ocular biometric system based on the fusion of left and right corneal shapes for identity authentication.

Results: For each individual, we had eight feature vectors (eight measures in two sessions) of size 36 (Zernike polynomial coefficients) from their corneal topographies. The experimental results on our cornea database constructed for this study showed encouraging performance of the proposed ocular biometric system with Equal Error Rate decreasing to 1.38% with the weighted-sum rule compared to the analysis of the left (4.5%) or right (3.7%)cornea alone.

Conclusions: The objective of this work was to investigate corneal topographyas an accurate biometric modality using shape discriminating features. Our idea was to propose an ocular multi-unit system based on the fusion of the left and right corneal shapes. The corneal feature extraction was done by Zernike polynomial decomposition. Multi-unit cornea fusion was performed at the matching score level to generate a unique score. This allowed a significative decrease of the EER to 1.38%.

Keywords: Ocular biometric; left cornea; right cornea; fusion; multi-unit system

doi: 10.21037/aes.2018.AB081
Cite this abstract as: Kihal N, Brunette I, Meunier J. Multi-unit ocular biometric system based on corneal shapes. Ann Eye Sci 2018;3:AB081.