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SFinGe

  • Reference work entry
Encyclopedia of Biometrics

Synonyms

Synthetic Fingerprint Generator

Definition

SFinGe (Synthetic Fingerprint Generator) is a fingerprint sample synthesis approach developed by the Biometric System Laboratory of the University of Bologna (Italy). It is available as a software program able to generate large databases of images very similar to human’s fingerprints, together with ground-truth data about their characteristics and features. These databases are particularly useful for developing, optimizing and testing fingerprint recognition systems and are being extensively used by industrial, academic and government organizations.

Overview and History

SFinGe (the Italian for sphinx, pronunciation sphin-je) is the acronym for Synthetic Fingerprint Generator. SFinGe can be used to easily create large databases of fingerprints, thus allowing recognition algorithms to be simply trained, tested and optimized. The images generated emulate fingerprints acquired with on-line sensors (see Fingerprint Acquisition) but, with...

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References

  1. Biometric System Laboratory (University of Bologna) web site, Available at: http://biolab.csr.unibo.it. Accessed January 2008

  2. Cappelli, R., Erol, A., Maio, D., Maltoni, D: “Synthetic Fingerprint-image Generation.” In: Proceedings of the 15th International Conference on Pattern Recognition, Barcelona, vol. 3, pp. 475–478 September (2000)

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  3. Maio, D., Maltoni, D., Cappelli, R., Wayman, J.L., Jain, A.K.: FVC2000: Fingerprint Verification Competition. IEEE Trans Pattern Anal Mach Intell 24(3), 402–412 (2002)

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  4. Cappelli, R., Maio, D., Maltoni, D: “Synthetic Fingerprint-Database Generation.” In: Proceedings of the 16th International Conference on Pattern Recognition, Québec City, vol. 3, pp. 744–747, August (2002)

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  5. Cappelli, R: Synthetic fingerprint generation, In: Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S. (eds.) Handbook of Fingerprint Recognition, Springer, New York, (2003)

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  6. Cappelli, R., Maio, D., Maltoni, D., (2004)“An Improved Noise Model for the Generation of Synthetic Fingerprints.” In: Proceedings Eighth International Conference on Control, Automation, Robotics and Vision (ICARCV2004), Kunming, China, December

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  7. Cappelli, R: “Use of Synthetic Data for Evaluating the Quality of Minutia Extraction Algorithms”, In: Proceedings of the Second NIST Biometric Quality Workshop, Gaithersburg, Maryland, November (2007)

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  8. Saito, M., Matsumoto, M: “SIMD-oriented Fast Mersenne Twister: a 128-bit Pseudorandom Number Generator”, Monte Carlo and Quasi-Monte Carlo Methods 2006, pp. 607–622. Springer, New York, (2008)

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  9. ISO/IEC 19794-2:2005, Information technology – Biometric data interchange formats – Part 2: Finger minutiae data

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  10. Cappelli, R., Maio, D., Maltoni, D., Wayman, J.L., Jain, A.K. Performance Evaluation of Fingerprint Verification Systems. IEEE Trans Pattern Anal Mach Intell. 28(1), 3–18 (2006)

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  11. Cappelli, R., Maio, D., Maltoni, D: “Indexing Fingerprint Databases for Efficient 1:N Matching.” In: Proceedings of the Sixth International Conference on Control, Automation, Robotics and Vision (ICARCV2000), Singapore, December (2000)

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  12. Minutiae Interoperability Exchange Test (MINEX) web site, Available at: http://fingerprint.nist.gov/minex04. Accessed January 2008

  13. Minutiae Template Interoperability Testing (MTIT) Project web site, Available at: http://www.mtitproject.com. Accessed January 2008

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Author information

Authors and Affiliations

  1. Biometric System Laboratory – DEIS – University of Bologna,  ,  

    Raffaele Cappelli

Authors
  1. Raffaele Cappelli
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Editor information

Editors and Affiliations

  1. Center for Biometrics and Security Research, Chinese Academy of Sciences, Beijing, China

    Stan Z. Li (Professor) (Professor)

  2. Departments of Computer Science & Engineering, Michigan State University, East Lansing, MI, USA

    Anil Jain (Professor) (Professor)

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© 2009 Springer Science+Business Media, LLC

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Cappelli, R. (2009). SFinGe. In: Li, S.Z., Jain, A. (eds) Encyclopedia of Biometrics. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-73003-5_8

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