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Definition
Biometric system evaluation is a procedure of quantifying the performance of a biometric recognition system under given conditions. The goal of such an evaluation is a comparison to another system, or a prediction of the system’s performance using unseen biometric data, collected under similar operating conditions.
Background
Biometric systems serve the purpose of assigning a class label to an acquired biometric data record. The procedure of assigning such a label always requires a decision. In the case of identity verification, this decision is binary and it reflects the difference between the genuine and the imposter identity claims. In the case of identification, a particular identity stands behind the class label. The core functional unit of a biometric system, responsible for taking the decision on assigning a particular class label, is a classifier. The goal of the design and...
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Recommended Reading
International Civil Aviation Organization, “ICAO Doc 9303, Machine Readable Travel Documents, Part 3, Machine Readable Official Travel Documents, Volume 2, Specifications for Electronically Enabled MRtds with Biometric Identification Capability”, third edition, 2008. Montreal: International Civil Aviation Organization
Phillips PJ, Martin A, Wilson CL, Przybocki M (2000) An introduction to evaluating biometric systems. Computer 33(2): 56–63
ISO/IEC 19795-2 (2007) Information technology – Biometric performance testing and reporting – Part 2: testing methodologies for technology and scenario evaluation. International Standards Organisation, Geneva
ISO 9241 (1998) Ergonomic requirements for office work with visual display terminals (VDTs) – Part 11: Guidance on usability
Kukula EP, Proctor RW (2009) Human-biometric sensor interaction: impact of training on biometric system and user performance. In: Human interface and the management of information. Information and interaction, Springer LNCS, 5618, Springer, Heidelberg, pp 168–177
Hicklin A, Watson C, Ulery B (2005) The myth of goats: how many people have fingerprints that are hard to match? NISTIR 7271, National Institute of Standards and Technology, Gaithersburg, USA
Richiardi J, Kryszczuk K, Drygajlo A (2007) Quality measures in unimodal and multimodal biometric verification. In: Proceedings of the 15th European signal processing conference (EUSIPCO), Poznan, Poland
Bengio S, Mariéthoz J, Keller M (2005) The expected performance curve. In: International conference on machine learning, ICML, Workshop on ROC analysis in machine learning, http://www.users.dsic.upv.es/∼flip/ROCML2005/papers.html
Gamassi M, Lazzaroni M, Misino M, Piuri V, Sana D, Scotti F (2004) Accuracy and performance of biometric systems. In: Proceedings of IMTC 2004 – Instrumentation and measurement technology conference, Como, Italy
Bailly-Bailliére E, Bengio S, Bimbot F, Hamouz M, Kittler J, Mariéthoz J, Matas J, Messer K, Popovici V, Porée F, Ruiz B, Thiran J-P (2003) The BANCA database and evaluation protocol. In: Kittler J, Nixon MS, (eds) Proceedings of 4th International conference on audio- and video-based biometric person authentication (AVBPA, 2003), vol LNCS 2688, Guildford, UK, pp 625–638
Doddington G, Liggett W, Martin A, Przybocki M, Reynolds DA (1998) Sheep, goats, lambs and wolves: a statistical analysis of speaker performance in the NIST 1998 speaker recognition evaluation. In: Proceedings of the 5th International Conference on spoken language processing (ICSLP), Sydney, Australia
Yager N, Dunstone T (2010) The biometric menagerie. IEEE Trans Pattern Anal Mach Intell 32(2):220–230
Dass SC, Zhu Y, Jain AK (2006) Validating a biometric authentication system: sample size requirements. IEEE Trans Pattern Anal Mach Intell 28(12):1902–1319
Mansfield AJ, Wayman JL (2002) Best practices in testing and reporting performance of biometric devices. NPL Report CMSC 14/02, Centre for Mathematics and Scientific Computing, National Physical Laboratory, Teddington, Middlesex, UK
Schuckers ME (2003) Using the beta-binomial distribution to assess performance of a biometric identification device. Int J Image Graph 3(3):523–529
FVC-onGoing: on-line evaluation of fingerprint recognition algorithms. https://www.biolab.csr.unibo.it/FVCOnGoing/UI/Form/Home.aspx. Accessed 01st May 2010
NIST Information Technology Laboratory, Information Access Division. Speaker Recognition Evaluation. http://www.itl.nist.gov/iad/mig/tests/sre/. Accessed 01st May 2010
Phillips PJ, Scruggs WT, O’Toole AJ, Flynn PJ, Bowyer KW, Schott CL, Sharpe M (2007) FRVT 2006 and ICE 2006 Large-scale results. Technical report NISTIR 7408, National Institute of Standards and Technology
Ortega-Garcia J et al (2010) The Multi-Scenario Multi-Environment BioSecure Multimodal Database (BMDB) IEEE Trans. Pattern Anal. Mach. Intell. 32(6):1097–1111
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Richiardi, J., Kryszczuk, K. (2011). Biometric Systems Evaluation. In: van Tilborg, H.C.A., Jajodia, S. (eds) Encyclopedia of Cryptography and Security. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-5906-5_729
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DOI: https://doi.org/10.1007/978-1-4419-5906-5_729
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