Fingerprint Synthesis

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.