Synonym
Expected performance or utility of fingerprint image in an automated comparison environment
Definition
The intrinsic characteristic of a biometric signal may be used to determine its suitability for further processing by the biometric system or assess its conformance to preestablished standards. The quality of a biometric signal is a numerical value (or a vector) that measures this intrinsic attribute. Quality score is a quantitative expression of the utility, or predicted performance of a biometric sample in a comparison environment. This means that finger image quality scores should correlate to the observed false match and false non-match rates of the samples.
Introduction
With an increase in the need for reliable identity authentication, biometric recognition systems have been increasingly deployed in several different applications: government applications such as national ID card, border control; and commercial applications, such as physical access control, e-commerce, or...
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition. Springer, New York (2003)
Grother, P., et al.: MINEX: Performance and Interoperability of the INCITS 378 Fingerprint Template. National Institute of Standards and Technology, NISTIR 7296 edn. (2005). http://fingerprint.nist.gov/minex04
Tabassi, E., Wilson, C., Watson, C.: Fingerprint Image Quality, NFIQ. National Institute of Standards and Technology, NISTIR 7151 edn. (2004)
Tabassi, E., Wilson, C.L.: A novel approach to fingerprint image quality. In: ICIP (2), pp. 37–40 (2005)
Tilton, C., et al.: The BioAPI Specification. American National Standards Institute, Inc. (2002)
Benini, D., et al.: ISO/IEC 29794-1 Biometric Sample Quality Standard: Framework. JTC1 / SC37 / Working Group 3 (2008). http://isotc.iso.org/isotcportal
Alonso-Fernandez, F., Fierrez, J., Ortega-Garcia, J., Gonzalez-Rodriguez, J., Fronthaler, H., Kollreider, K., Bigun, J.: A Comparative study of fingerprint image-quality estimation methods. IEEE Trans. Inform. Forens. Secur. 2, 734–743 (2007)
Lim, E., Jiang, X., Yau, W.: Fingerprint image quality and validity analysis. In: IEEE proceedings of International Conference on Image Processing (ICIP), pp. 469–472. New York, USA (2002)
Chen, Y., Dass, S.C., Jain, A.K.: Fingerprint quality indices for predicting authentication performance. In: AVBPA, pp. 160–170 (2005)
Shen, L., Kot, A.C., Koo, W.M.: Quality measures of fingerprint images. In: AVBPA, pp. 266–271 (2001)
Ratha, N., Bolle, R.: Automatic Fingerprint Recognition Systems. Springer, New York (2004)
Lim, E., Toh, K.A., Saganthan, P.N., Jiang, X., Yau, W.Y.: Fingerprint image quality analysis. In: ICIP, pp. 1241–1244 (2004)
Chen, T.P., Jiang, X., Yau, W.Y.: Fingerprint image quality analysis. In: ICIP, pp. 1253–1256 (2004)
Bolle, R., et al.: System and methods for determining the quality of fingerprint images. US Patent 596356 (1999)
Hong, L., Wan, Y., Jain, A.K.: Fingerprint image enhancement: algorithm and performance evaluation. IEEE Trans. Pattern Analy. Mach. Intell. 20(8), 777–789 (1998)
Nill, N., Bouzas, B.H.: Objective image quality measure derived from digital image power spectra. Opt. Eng. 31(4), 813–825 (1992)
National Institute of Standards and Technology: NIST Biometric Image Software (NBIS) (2008). http://www.itl.nist.gov/iad/894.03/nigos/nbis.html
Ko, T., Krishnan, R.: Monitoring and reporting of fingerprint image quality and match accuracy for a large user application. In: Proceedings of the 33rd Applied Image Pattern Recognition Workshop, pp. 159–164. IEEE Computer Society (2004)
Tabassi, E., Grother, P.: Quality Summarization: Recommendations on Enterprise-wide Biometric Quality Summarization. National Institute of Standards and Technology, NISTIR 7244 edn. (2007)
Wein, L.M., Baveja, M.: Using fingerprint image quality to improve the identification performance of the u.s. visit program. In: Proceedings of the National Academy of sciences (2005). www.pnas.org/cgi/doi/10.1073/pnas.0407496102
Fierrez-Aguilar, J., Ortega-Garcia, J., Gonzalez-Rodriguez, J., Bigun, J.: Discriminative multimodal biometric authentication based on quality measures. Pattern Recogn. 38(5), 777–779 (2005)
Tabassi, E., Quinn, G.W., Grother, P.: When to fuse two biometrics. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition CVPR-06. New York (2006). Biometric Workshop
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer Science+Business Media, LLC
About this entry
Cite this entry
Tabassi, E., Grother, P. (2009). Fingerprint Image Quality. In: Li, S.Z., Jain, A. (eds) Encyclopedia of Biometrics. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-73003-5_52
Download citation
DOI: https://doi.org/10.1007/978-0-387-73003-5_52
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-73002-8
Online ISBN: 978-0-387-73003-5
eBook Packages: Computer ScienceReference Module Computer Science and Engineering