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Periocular-based biometrics robust to eye rotation based on polar coordinates

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Abstract

Conventional iris recognition requires a high-resolution camera equipped with a zoom lens and a near-infrared illuminator to observe iris patterns. Moreover, with a zoom lens, the viewing angle is small, restricting the user’s head movement. To address these limitations, periocular recognition has recently been studied as biometrics. Because the larger surrounding area of the eye is used instead of iris region, the camera having the high-resolution sensor and zoom lens is not necessary for the periocular recognition. In addition, the image of user’s eye can be captured by using the camera having wide viewing angle, which reduces the constraints to the head movement of user’s head during the image acquisition. Previous periocular recognition methods extract features in Cartesian coordinates sensitive to the rotation (roll) of the eye region caused by in-plane rotation of the head, degrading the matching accuracy. Thus, we propose a novel periocular recognition method that is robust to eye rotation (roll) based on polar coordinates. Experimental results with open database of CASIA-Iris-Distance database (CASIA-IrisV4) show that the proposed method outperformed the others.

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Acknowledgments

This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2015-H8501-15-1014) supervised by the IITP (Institute for Information & communications Technology Promotion). Portions of the research in this paper use the CASIA-IrisV4 collected by the Chinese Academy of Sciences' Institute of Automation (CASIA).

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Authors and Affiliations

  1. Division of Electronics and Electrical Engineering, Dongguk University, Seoul, Republic of Korea

    So Ra Cho, Gi Pyo Nam, Kwang Yong Shin, Dat Tien Nguyen, Tuyen Danh Pham & Kang Ryoung Park

  2. Department of Computer Science, Sangmyung University, Seoul, Republic of Korea

    Eui Chul Lee

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  1. So Ra Cho
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  2. Gi Pyo Nam
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  3. Kwang Yong Shin
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  4. Dat Tien Nguyen
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  5. Tuyen Danh Pham
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  6. Eui Chul Lee
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  7. Kang Ryoung Park
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Correspondence to Kang Ryoung Park.

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Cho, S.R., Nam, G.P., Shin, K.Y. et al. Periocular-based biometrics robust to eye rotation based on polar coordinates. Multimed Tools Appl 76, 11177–11197 (2017). https://doi.org/10.1007/s11042-015-3052-0

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  • DOI: https://doi.org/10.1007/s11042-015-3052-0

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