The Quality of Fingerprint Scanners and Its Impact on the Accuracy of Fingerprint Recognition Algorithms

  • Raffaele Cappelli
  • Matteo Ferrara
  • Davide Maltoni
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4105)


It is well-known that in any biometric systems the quality of the input data has a strong impact on the accuracy that the system may provide. The quality of the input depends on several factors, such as: the quality of the acquisition device, the intrinsic quality of the biometric trait, the current conditions of the biometric trait, the environment, the correctness of user interaction with the device, etc. Much research is being carried out to quantify and measure the quality of biometric data [1] [2]. This paper focuses on the quality of fingerprint scanners and its aim is twofold: i) measuring the correlation between the different characteristics of a fingerprint scanner and the performance they can assure; ii) providing practical ways to measure such characteristics.


Modulation Transfer Function Biometric System Fingerprint Image Biometric Trait Objective Image Quality 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Tabassi, E., Wilson, C.L., Watson, C.I.: Fingerprint Image Quality. Nist research report NISTIR 7151 (August 2004)Google Scholar
  2. 2.
    Chen, Y., Dass, S., Jain, A.: Fingerprint Quality Indices for Predicting Authentication Performance. In: Kanade, T., Jain, A., Ratha, N.K. (eds.) AVBPA 2005. LNCS, vol. 3546, pp. 160–170. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  3. 3.
    Department of Justice F.B.I., Electronic Fingerprint Transmission Specification, CJIS-RS-0010 (V7) (January 1999)Google Scholar
  4. 4.
    NIST, IAFIS Image Quality Specifications for Single Finger Capture Devices, NIST White Paper (working document), available at:
  5. 5.
    NIST Personal Identification Verification Program web site,
  6. 6.
    FVC 2006 web site (2006),
  7. 7.
    Nill, N.B., Bouzas, B.H.: Objective Image Quality Measure Derived from Digital Image Power Spectra. Optical Engineering 31(4), 813–825 (1992)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Raffaele Cappelli
    • 1
  • Matteo Ferrara
    • 1
  • Davide Maltoni
    • 1
  1. 1.Biometric System Laboratory – DEISUniversity of BolognaCesenaItaly

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