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A Scheme for Fingerphoto Recognition in Smartphones

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Selfie Biometrics

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

Touchless technologies for fingerphoto recognition based on smartphones can be considered selfie biometrics, in which a user captures images of his or her own biometric traits by using the integrated camera in a mobile device (here referred to as selfie fingerprint biometrics). Such systems mitigate the limitations of leaving latent fingerprints, dirt on the acquisition device released by the fingers, and skin deformations induced by touching an acquisition surface associated with a touch ID-based system. Furthermore, the use of the integrated camera to perform biometric acquisition bypasses the need of a dedicated fingerprint scanner. With respect to touch-based fingerprint recognition systems, selfie fingerprint biometrics require ad hoc methods for most steps of the recognition process. This is because the images captured using smartphone cameras present more complex backgrounds, lower visibility of the ridges, reflections, perspective distortions, and nonuniform resolutions. Selfie fingerprint biometric methods are usually less accurate than touch-based methods, but their performance can be satisfactory for a wide variety of security applications. This chapter presents a comprehensive literature review of selfie fingerprint biometrics. First, we introduce selfie fingerprint biometrics and touchless fingerprint recognition methods. Second, we describe the technological aspects of the different steps of the recognition process. Third, we analyze and compare the performances of recent methods proposed in the literature.

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Acknowledgements

This work was supported in part by the Italian Ministry of Research as part of the PRIN 2015 project COSMOS (201548C5NT).

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Authors and Affiliations

  1. Department of Computer Science, Università degli Studi di Milano, Via Celoria 18, 20133, Milano, Italy

    Ruggero Donida Labati, Angelo Genovese, Vincenzo Piuri & Fabio Scotti

Authors
  1. Ruggero Donida Labati
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  2. Angelo Genovese
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  3. Vincenzo Piuri
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  4. Fabio Scotti
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Corresponding author

Correspondence to Ruggero Donida Labati .

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Editors and Affiliations

  1. Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS, USA

    Ajita Rattani

  2. Department of Computer Science and Electrical Engineering, University of Missouri-Kansas City, Kansas City, MO, USA

    Reza Derakhshani

  3. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA

    Arun Ross

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Donida Labati, R., Genovese, A., Piuri, V., Scotti, F. (2019). A Scheme for Fingerphoto Recognition in Smartphones. In: Rattani, A., Derakhshani, R., Ross, A. (eds) Selfie Biometrics. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-030-26972-2_3

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  • DOI: https://doi.org/10.1007/978-3-030-26972-2_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26971-5

  • Online ISBN: 978-3-030-26972-2

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