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Presenting the 1st definitive examine of the topic, this Handbook of Biometric Anti-Spoofing experiences the state-of-the-art in covert assaults opposed to biometric structures and in deriving countermeasures to those assaults. themes and lines: offers an in depth advent to the sphere of biometric anti-spoofing and an intensive overview of the linked literature; examines spoofing assaults opposed to 5 biometric modalities, particularly, fingerprints, face, iris, speaker and gait; discusses anti-spoofing measures for multi-model biometric platforms; experiences assessment methodologies, overseas criteria and felony and moral matters; describes present demanding situations and indicates instructions for destiny study; offers the newest paintings from an international number of specialists within the box, together with participants of the TABULA RASA project.
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Extra info for Handbook of Biometric Anti-Spoofing: Trusted Biometrics under Spoofing Attacks
1. 2 (Fig. 2). 2 During the writing of this chapter the 2013 LivDet edition was being held. The DB used in the evaluation will be made public on the web site of the competition once the final results are published. it/LivDet09/. php. es/. 3 Fingerprint Anti-spoofing in Biometric Systems (FLAT OPTICAL SENSOR) IDENTIX DFR2100 (FLAT OPTICAL SENSOR) Silicone – Coop. Gelatin – Coop. BIOMETRIKA FX2000 41 PRECISE SC 100 (FLAT CAPACITIVE SENSOR) REAL FAKE Silicone – Non Coop. Fig. 1 Typical examples of real and fake fingerprints that may be found in the ATVS-FFp DB and the LivDet 2009 and 2011 DBs described in Sect.
Schwarz L (2009) An amino acid model for latent fingerprints on porous surfaces. J Forensic Sci 54(6):1323–1326 35. Hildebrandt M, Kiltz S, Dittmann J, Vilhauer C (2011) Malicious fingerprint traces: a proposal for an automated analysis of printed amino acid dots using houghcircles. In: Thirteenth ACM multimedia workshop on multimedia and security, pp 33–39 36. Hildebrandt M, Kiltz S, Sturm J, Dittmann J, Vielhauer C (2012) High-resolution printed amino acid traces: a first-feature extraction approach for fingerprint forgery detection.
2). Morisod also showed that on marks developed with DFO (an amino acid reagent), a clear difference in the amount of residue and its distribution can be seen (Fig. 3). This is due to the difficulty on forgeries to reproduce the distribution of the fingerprint eccrine residue along the ridges. Eccrine residue being secreted through the sweat pores of the friction ridge skin, a richer concentration is expected at the location of pores, giving on genuine marks a detection of ridges that appears as a succession of dotted points, especially when visualised in photoluminescence mode.