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International Joint Conference on Computational Intelligence

IJCCI 2017: Computational Intelligence pp 263–279Cite as

Assessing Transfer Learning on Convolutional Neural Networks for Patch-Based Fingerprint Liveness Detection

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 829))

Abstract

Fingerprint based biometric identification systems are vulnerable to spoofing attacks that involve the use of fake replicas of real fingerprints. The resulting security issues can be mitigated through the development of software modules capable of detecting the liveness of an input image and, thus, of discarding fake fingerprints before the classification step. In this work we present a fingerprint liveness detection method that combines a patch-based voting approach with Transfer Learning techniques. Fingerprint images are first segmented to discard background information. Then, small-sized foreground patches are extracted and processed by popular Convolutional Neural Network models, whose pre-trained versions were adapted to the problem at hand. Finally, the individual patch scores are combined to obtain the fingerprint label. Experimental results on well-established benchmarks show the promising performance of the proposed method compared with several state-of-the-art algorithms.

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Notes

  1. 1.

    We underline that, while all methods have been tested with LivDet2013, some results are not available for LivDet2011.

  2. 2.

    Numbers reported differs from those in [19] due to some code optimization.

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Acknowledgements

Computational resources were provided by HPC@POLITO, a project of Academic Computing within the Department of Control and Computer Engineering at the Politecnico di Torino (http://www.hpc.polito.it).

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Authors and Affiliations

  1. Department of Control and Computer Engineering, Politecnico di Torino, Turin, Italy

    Amirhosein Toosi, Sandro Cumani & Andrea Bottino

Authors
  1. Amirhosein Toosi
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  2. Sandro Cumani
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  3. Andrea Bottino
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Corresponding author

Correspondence to Andrea Bottino .

Editor information

Editors and Affiliations

  1. IUT Sénart, Université Paris-Est Créteil (UPEC), Créteil, France

    Christophe Sabourin

  2. Department of Computer Architecture and Technology, University of Granada, Granada, Spain

    Juan Julian Merelo

  3. Université Paris-Est Créteil (UPEC), Créteil, France

    Kurosh Madani

  4. University of Reading, Reading, UK

    Kevin Warwick

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Toosi, A., Cumani, S., Bottino, A. (2019). Assessing Transfer Learning on Convolutional Neural Networks for Patch-Based Fingerprint Liveness Detection. In: Sabourin, C., Merelo, J.J., Madani, K., Warwick, K. (eds) Computational Intelligence. IJCCI 2017. Studies in Computational Intelligence, vol 829. Springer, Cham. https://doi.org/10.1007/978-3-030-16469-0_14

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