Multimodal ocular biometrics approach: A feasibility study

Growing efforts have been concentrated on the development of alternative biometric recognition strategies, the intended goal to increase the accuracy and counterfeit-resistance of existing systems without increased cost. In this paper, we propose and evaluate a novel biometric approach using three fundamentally different traits captured by the same camera sensor. Considered traits include: 1) the internal, non-visible, anatomical properties of the human eye, represented by Oculomotor Plant Characteristics (OPC); 2) the visual attention strategies employed by the brain, represented by Complex Eye Movement patterns (CEM); and, 3) the unique physical structure of the iris. Our experiments, performed using a low-cost web camera, indicate that the combined ocular traits improve the accuracy of the resulting system. As a result, the combined ocular traits have the potential to enhance the accuracy and counterfeit-resistance of existing and future biometric systems.

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