Template Selection by Editing Algorithms: A Case Study in Face Recognition

  • Biagio Freni
  • Gian Luca Marcialis
  • Fabio Roli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5342)


In this paper, we consider the problem of template selection in biometric systems as analogous to the problem, called “editing”, of selecting representative prototypes when using the 1-Nearest Neighbour classifier (NN). Four editing algorithms are used and compared by experiments with state-of-the-art template selection algorithms. Experiments are performed on a benchmark face data set. Reported results show pros and cons of editing algorithms for template selection in biometric systems.


Nearest neighbour biometrics face recognition template selection 


  1. 1.
    Jain, A.K., Pankanti, S. (eds.): Biometrics: Personal Identification in Networked society. Kluwer Academic Publishers, Dordrecht (1999)Google Scholar
  2. 2.
    Uludag, U., Ross, A., Jain, A.K.: Biometric template selection and update: a case study in fingerprints. Pattern Recognition 37(7), 1533–1542 (2004)CrossRefzbMATHGoogle Scholar
  3. 3.
    Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification. John Wiley & Sons, Chichester (2001)zbMATHGoogle Scholar
  4. 4.
    Koutroumbas, K., Theodoridis, S.: Pattern Recognition. Academic Press, London (2006)zbMATHGoogle Scholar
  5. 5.
    Randall Wilson, D., Martinez, T.R.: Reduction Techniques for Instance-Based Learning Algorithms,
  6. 6.
    Hart, P.E.: The Condensed Nearest Neighbor Rule. IEEE Transactions on Information Theory 14, 515–516Google Scholar
  7. 7.
    Ritter, G., Woodruff, H., Lowry, S., Isenhour, T.: An algorithm for a selective nearest neighbor decision rule. IEEE Transactions on Information Theory 21(6), 665–669Google Scholar
  8. 8.
    Gates, G.W.: The Reduced Nearest Neighbor Rule. IEEE Transactions on Information Theory 18(3), 431–433Google Scholar
  9. 9.
    Wilson, D.L.: Asymptotic properties of nearest neighbor rules using edited data. IEEE Transactions on System, Man and Cybernetics 2, 408–421 (1972)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Jain, A.K., Nadakumar, K., Ross, A.: Score Normalization in Multimodal Biometrics Systems. Pattern Recognition Letters (2005)Google Scholar
  11. 11.
    Jain, A.K., Dubes, R.C.: Algorithms for Clustering Data. Prentice-Hall, Englewood Cliffs (1988)zbMATHGoogle Scholar
  12. 12.
    Jain, A.K., Hong, L., Bolle, R.: On-line Fingerprint Verification. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(4), 302–314 (1997)CrossRefGoogle Scholar
  13. 13.
  14. 14.
    Roli, F., Marcialis, G.L.: Semi-supervised PCA-based face recognition using self-training. In: Yeung, D.-Y., Kwok, J.T., Fred, A., Roli, F., de Ridder, D. (eds.) SSPR 2006 and SPR 2006. LNCS, vol. 4109, pp. 560–568. Springer, Heidelberg (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Biagio Freni
    • 1
  • Gian Luca Marcialis
    • 1
  • Fabio Roli
    • 1
  1. 1.Department of Electrical and Electronic Engineering Piazza d’ArmiUniversity of CagliariCagliariItaly

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