Encyclopedia of Biometrics

2009 Edition
| Editors: Stan Z. Li, Anil Jain

Fingerprint Matching, Automatic

  • Jie Tian
  • Yangyang Zhang
  • Kai Cao
Reference work entry
DOI: https://doi.org/10.1007/978-0-387-73003-5_54

Synonyms

 Fingerprint comparing; Automatic

Definition

In contrast to manual fingerprint matching, automatic fingerprint matching can be efficiently operated on a computing machine following a series of preset procedures. Automatic matching compares two given fingerprint templates (raw images or extracted features) and returns their similarity score (in a continuous range) or a binary decision (matched/non-matched).

Introduction

With the increasing expansion of large-scale databases, manual fingerprint matching cannot satisfy the demand of efficiency in many applications. Automatic fingerprint matching simulates how human experts compare the fingerprints to measure the similarity between two given fingerprint templates or to determine whether they come from the same finger [1]. For most fingerprint matching procedures, experts calculate the similarity score of two templates and give the final judgment with a preset threshold. If the score exceeds the threshold, the compared templates...

This is a preview of subscription content, log in to check access

References

  1. l.
    Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition. Springer, Berlin (2003)MATHGoogle Scholar
  2. 2.
    Ross, A., Jain, A.K.: Biometric sensor interoperability: a case study in fingerprints, BioAW 2004. LNCS 3087, 134–145 (2004)Google Scholar
  3. 3.
    Bazen, A.M., Gerez, S.H.: An intrinsic coordinate system for fingerprint matching. In: Third International Conference on Audio- and Video-Based Biometric Person Authentication, Halmstad, Sweden (2001)Google Scholar
  4. 4.
    Luo, X.P., Tian, J., Wu, Y.: A Minutia matching algorithm in fingerprint verification. Fifteenth ICPR 4, 833–836 (2000)Google Scholar
  5. 5.
    Jain, A.K., Lin, H., Bolle, R.: On-line fingerprint verification. IEEE Trans. Pattern Recogn. Machine Intell. 19(4), 302–314 (1997)CrossRefGoogle Scholar
  6. 6.
    Kovacs-Vajna, Z.M.: A fingerprint verification system based on triangular matching and dynamic time warping. IEEE Trans. Pattern Recogn. Machine Intell. 22(11), 1266–1276 (2000)CrossRefGoogle Scholar
  7. 7.
    Chen, X.J., Tian, J., Yang, X.: A new algorithm for distorted fingerprints matching based on normalized fuzzy similarity measure. IEEE Trans. Image Process. 15(3), 767–776 (2006)CrossRefGoogle Scholar
  8. 8.
    Bazen, A.M., Gerez, S.H.: Fingerprint matching by thin-plate spline modelling of elastic deformations. Pattern Recogn. 36(8), 1859–1867 (2003)CrossRefGoogle Scholar
  9. 9.
    Ross, A., Dass, S., Jain, A.K.: A deformable model for fingerprint matching. Pattern Recogn. 38(1), 95–103 (2005)CrossRefGoogle Scholar
  10. 10.
    He, Y.L., Tian, J., Li, L., Yang, X.: Fingerprint matching based on global comprehensive similarity. IEEE Trans. Pattern Analy. Machine Intell. 28(6), 850–862 (2006)CrossRefGoogle Scholar
  11. 11.
    Jain, A.K., Chen, Y., Demirkus, M.: Pores and ridges: high-resolution fingerprint matching using level 3 features. IEEE Trans. Pattern Recogn. Machine Intell. 29(1), 15–27 (2007)CrossRefGoogle Scholar
  12. 12.
    Jain, A.K., Prabhakar, S., Lin, H., Pankanti, S.: Filterbank-based fingerprint matching. IEEE Trans. Image Process. 9(5), 846–859 (2000)CrossRefGoogle Scholar
  13. 13.
    Gu, J., Zhou, J., Yang, C.: Fingerprint recognition by combining global structure and local cues. IEEE Trans. Image Process 15(7), 1952–1964 (2006)CrossRefGoogle Scholar
  14. 14.
    Wang, X.C., Li, J.W., Niu, Y.M.: Fingerprint matching using OrientationCodes and PolyLines. Pattern Recogn. 40(11), 3164–3177 (2007)MATHCrossRefGoogle Scholar
  15. 15.
  16. 16.
    Cappelli, R., Maio, D., Maltoni, D., Wayman, J.L., Jain, A.K.: Performance evaluation of fingerprint verification systems. IEEE Trans. Pattern Recogn. Machine Intell. 28(1), 3–18 (2006)CrossRefGoogle Scholar
  17. 17.
  18. 18.
    Ross, A., Jain, A.K.: Biometric sensor interoperability: a case study in fingerprints. Proc. Biometric Authentication: ECCV 2004 International Workshop 3087, 134–145 (2004)Google Scholar
  19. 19.
    Bolle, R.M., Ratha, N.K., Pankanti, S.: An evaluation of error confidence interval estimation methods. Fifteenth ICPR 3, 103–106 (2004)Google Scholar
  20. 20.
    Ross, A., Jain, A.K., Reisman, J.: A hybrid fingerprint matcher. Pattern Recogn. 36(7), 1661–1673 (2003)CrossRefGoogle Scholar
  21. 21.
    Bhakar, S., Jain, A.K.: Decision-level fusion in fingerprint verification. Pattern Recogn. 35(4), 861–874 (2002)CrossRefGoogle Scholar
  22. 22.
    Chen, X.J., Tian, J., Yang, X. An algorithm for distorted fingerprint matching based on local triangle features set. IEEE Trans. Inform. Forensics Security 1(2), 169–177 (2006)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Jie Tian
    • 1
  • Yangyang Zhang
    • 1
  • Kai Cao
    • 1
  1. 1.Center for Biometrics and Security Research & The Key Laboratory of Complex System and Intelligence Science Chinese Academy of SciencesInstitute of Automation Zhingguancun DongluBeijingChina