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A comprehensive multimodal eye recognition

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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.

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Acknowledgments

The authors would like to acknowledge the Department of Computer Science at the University of Beira Interior for providing the UBIRIS database [5]. We would also like to thank the people who contributed their data for IUPUI multi-wavelength database.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Purdue School of Engineering and Technology, Indiana University–Purdue University Indianapolis, Indianapolis, IN, 46202, USA

    Zhi Zhou, Eliza Y. Du & N. Luke Thomas

  2. School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, 47907, USA

    Edward J. Delp

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  1. Zhi Zhou
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  2. Eliza Y. Du
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  3. N. Luke Thomas
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  4. Edward J. Delp
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Correspondence to Eliza Y. Du.

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Zhou, Z., Du, E.Y., Thomas, N.L. et al. A comprehensive multimodal eye recognition. SIViP 7, 619–631 (2013). https://doi.org/10.1007/s11760-013-0468-8

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  • DOI: https://doi.org/10.1007/s11760-013-0468-8

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