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Fast periocular authentication in handheld devices with reduced phase intensive local pattern

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Abstract

To ensure highest security in handheld devices, biometric authentication has emerged as a reliable methodology. Deployment of mobile biometric authentication struggles due to computational complexity. For a fast response from a mobile biometric authentication method, it is desired that the feature extraction and matching should take least time. In this article, the periocular region captured through frontal camera of a mobile device is considered under investigation for its suitability to produce a reduced feature that takes least time for feature extraction and matching. A recently developed feature Phase Intensive Local Pattern (PILP) is subjected to reduction giving birth to a feature termed as Reduced PILP (R-PILP), which yields a matching time speed-up of 1.56 times while the vector is 20% reduced without much loss in authentication accuracy. The same is supported by experiment on four publicly available databases. The performance is also compared with one global feature: Phase Intensive Global Pattern, and three local features: Scale Invariant Feature Transform, Speeded-up Robust Features, and PILP. The amount of reduction can be varied with the requirement of the system. The amount of reduction and the performance of the system bears a trade-off. Proposed R-PILP attempts to make periocular suitable for mobile devices.

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Acknowledgment

The research is funded by Grant no. 12(5)/2012-ESD by Department of Electronics and Information Technology, Government of India. This research is an extension to:

S. Bakshi, P.K. Sa, and B. Majhi. A Novel Phase-intensive Local Pattern for Periocular Recognition under Visible Spectrum. Biocybernetics and Biomedical Engineering 35(1):30–44, 2015. doi:10.1016/j.bbe.2014.05.003.

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Authors and Affiliations

  1. Department of Computer Science & Engineering, National Institute of Technology, Rourkela, Odisha, 769 008, India

    Sambit Bakshi, Pankaj K. Sa, Soubhagya Sankar Barpanda & Banshidhar Majhi

  2. Cornell University, Ithaca, NY, USA

    Haoxiang Wang

  3. GoPerception Laboratory, New York, NY, USA

    Haoxiang Wang

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  1. Sambit Bakshi
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  2. Pankaj K. Sa
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  4. Soubhagya Sankar Barpanda
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  5. Banshidhar Majhi
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Correspondence to Sambit Bakshi.

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Bakshi, S., Sa, P.K., Wang, H. et al. Fast periocular authentication in handheld devices with reduced phase intensive local pattern. Multimed Tools Appl 77, 17595–17623 (2018). https://doi.org/10.1007/s11042-017-4965-6

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  • DOI: https://doi.org/10.1007/s11042-017-4965-6

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