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Classify NIR Iris Images Under Alcohol/Drugs/Sleepiness Conditions Using a Siamese Network

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Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications (CIARP 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14469))

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Abstract

This paper proposes a biometric application for iris capture devices using a Siamese network based on an EfficientNetv2 and a triplet loss function to classify iris NIR images captured under alcohol/drugs/sleepiness conditions. The results show that our model can detect the “Fit/Unfit” alertness condition from iris samples captured after alcohol, drug consumption, and sleepiness conditions robustly with an accuracy of 87.3% and 97.0% for Fit/Unfit, respectively. The sleepiness condition is the most challenging, with an accuracy of 72.4%. The Siamese model uses a smaller number of parameters than the standard Deep learning Network algorithm. This work complements and improves the literature on biometric applications for developing an automatic system to classify “Fitness for Duty” using iris images and prevent accidents due to alcohol/drug consumption and sleepiness.

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Notes

  1. 1.

    https://www.emcdda.europa.eu/publications/data-fact-sheets/european-web-survey-drugs-2021-top-level-findings-eu-21-switzerland_en.

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Acknowledgment

This work is supported by the German Federal Ministry of Education and Research and the Hessen State Ministry for Higher Education, Research and the Arts within their joint support of the National Research Center for Applied Cybersecurity ATHENE.

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Authors and Affiliations

  1. da/sec-Biometrics and Internet Security Research Group, Hochschule Darmstadt, Darmstadt, Germany

    Juan Tapia & Christoph Busch

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  1. Juan Tapia
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  2. Christoph Busch
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Correspondence to Juan Tapia .

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Editors and Affiliations

  1. Polytechnic Institute of Coimbra, Coimbra Institute of Engineering, Coimbra, Portugal

    Verónica Vasconcelos

  2. Polytechnic Institute of Coimbra, Coimbra Institute of Engineering, Coimbra, Portugal

    Inês Domingues

  3. Polytechnic Institute of Coimbra, Coimbra Institute of Engineering, Coimbra, Portugal

    Simão Paredes

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Tapia, J., Busch, C. (2024). Classify NIR Iris Images Under Alcohol/Drugs/Sleepiness Conditions Using a Siamese Network. In: Vasconcelos, V., Domingues, I., Paredes, S. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2023. Lecture Notes in Computer Science, vol 14469. Springer, Cham. https://doi.org/10.1007/978-3-031-49018-7_41

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  • DOI: https://doi.org/10.1007/978-3-031-49018-7_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-49017-0

  • Online ISBN: 978-3-031-49018-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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