A comprehensive multimodal eye recognition

Abstract

Iris recognition is tested to be one of the most reliable approaches for automatic personal recognition under the infrared light. However, it is challenging and difficult to acquire good quality iris patterns of dark color eyes in the visible wavelengths. Sclera recognition can achieve good recognition accuracy in the visible spectrum, but the performance will drop when the sclera pattern is saturated. In this paper, we proposed a comprehensive multimodal eye recognition system that uses both iris and sclera patterns for recognition from the same eye image. The experimental results show that the proposed multimodal frontal eye recognition method can achieve better recognition accuracy than unimodal iris or sclera recognition. In addition, we propose a multimodal multi-angle eye recognition system that can further improve the recognition accuracy.