Book cover Handbook of Fingerprint Recognition pp 385–426Cite as Fingerprint Synthesis Davide Maltoni, Dario Maio, Anil K. Jain & Jianjiang Feng Chapter First Online: 05 July 2022 253 Accesses Abstract Synthetic fingerprints, when properly generated, represent a reasonable substitute for real fingerprints for the design, training, and benchmarking of fingerprint recognition algorithms. This approach is particularly useful to deal with emerging privacy regulations (e.g., EU-GDPR) limiting the use of personally identifiable information. This chapter introduces fingerprint synthesis and focuses on the two main categories of generation approaches: (i) first generate a master fingerprint and then derive multiple impressions (e.g., SFinGe); (ii) generative models (e.g., GAN) for the direct synthesis of fingerprint images. Validation of synthetic generators through large scale experiments is finally presented.

Raffaele Cappelli (2022). Fingerprint Synthesis. Berlin : Springer [10.1007/978-3-030-83624-5_7].

Fingerprint Synthesis

Raffaele Cappelli
Primo
2022

Abstract

Book cover Handbook of Fingerprint Recognition pp 385–426Cite as Fingerprint Synthesis Davide Maltoni, Dario Maio, Anil K. Jain & Jianjiang Feng Chapter First Online: 05 July 2022 253 Accesses Abstract Synthetic fingerprints, when properly generated, represent a reasonable substitute for real fingerprints for the design, training, and benchmarking of fingerprint recognition algorithms. This approach is particularly useful to deal with emerging privacy regulations (e.g., EU-GDPR) limiting the use of personally identifiable information. This chapter introduces fingerprint synthesis and focuses on the two main categories of generation approaches: (i) first generate a master fingerprint and then derive multiple impressions (e.g., SFinGe); (ii) generative models (e.g., GAN) for the direct synthesis of fingerprint images. Validation of synthetic generators through large scale experiments is finally presented.
2022
Handbook of Fingerprint Recognition
385
426
Raffaele Cappelli (2022). Fingerprint Synthesis. Berlin : Springer [10.1007/978-3-030-83624-5_7].
Raffaele Cappelli
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/899074
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