Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
권호 표지
DOI QR코드

DOI QR Code

Dynamic Thresholding Scheme for Fingerprint Identification

지문 식별을 위한 동적 임계치 설정방법

  • 김경민 (전남대학교 전기전자통신컴퓨터공학부) ;
  • 이범 (전남대학교 전기전자통신컴퓨터공학부) ;
  • 박중조 (경상대학교 제어계측공학과) ;
  • 정순원 ((주) Ria Soft)
  • Received : 2012.02.08
  • Accepted : 2012.07.31
  • Published : 2012.09.01
Download PDF
⟨ Previous Next ⟩

Abstract

This paper proposes dynamic thresholding scheme for fingerprint identification. As a user authentication method by fingerprint recognition technology, verification method based on 1:1 matching was mainly used in the past, but identification method based on 1:N matching is generally used recently. The control of the value of FAR is very important in the application areas such as access control and time attendance systems. This paper proposes dynamic thresholding scheme which could properly control the value of FAR according to the field of applications and size of the fingerprints database.

Keywords

References

  1. A. K. Jain, R. Bolle, and S. Pankaniti(Eds), Biometrics: Personal Identification in Networked Society, Kluwer Academic, NewYork, 1999.
  2. N. K. Ratha, S. Y. Chen, and A. K. Jain, "Adaptive flow orientation-based feature extraction in fingerprint images," Pattern Recognition, vol. 28, no. 11, pp. 1657-1672, 1995. https://doi.org/10.1016/0031-3203(95)00039-3
  3. C. Arcelli and G. S. D. Baja, "A width independent fast thinning algorithm," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 4, no. 7, pp. 463-474, 1984.
  4. D. Maltoni, D. Maio, A. K. Jain, and S. Prabhakar, Handbook of Fingerprint Recognition, Springer, 2003.
  5. A. Ranade and A. Rosenfeld, "Point pattern matching by relaxation," Pattern Recognition, vol. 12, no. 2, pp. 269-275, 1993.
  6. J. H. Wegstein, "An automated fingerprint identification system," U.S. Government Publication, Washington, DC: U.S. Dept. of Commerce, National Bureau of Standards, 1982.
  7. J. H. Moon and H. I. Kim, "Scoring method of fingerprint image quality using classified block-level characteristics," Journal of the Korea Institute of Information Security and Cryptology (in Korean), vol. 17, no. 2, pp. 29-40, 2007.
  8. Y. N. Shin, W. J. Sung, and S. W. Jung, "Quality assessment of fingerprint images and correlation with recognition performance," Journal of the Korea Institute of Information Security and Cryptology (in Korean), vol. 18, no. 3, pp. 61-68, 2008.
  9. B. M. Sullivan and S. P. Hsu, "Biometric score normalizer," U.S. Patent Office, U.S. Patent Issued, US 6,591,224, 2003.
  10. P. Z. Lo, "Dynamic thresholding for a fingerprint matching system," U.S. Patent Office, U.S. Patent Issued, US 7,257,241, 2007.
  11. G. T. Candela, P. J. Grother, C. I. Watson, R. Wilkinson, and C. L. Wilson, "PCASYS - A pattern-level classification automation system for fingerprints," Tech. Report : NIST TR 5647, Aug. 1995.
  12. R. Cappelli, A. Lumini, D. Maio, and D. Maltoni, "Fingerprint classification by directional image partitioning," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 5, pp. 402-421, 1999. https://doi.org/10.1109/34.765653
  13. K. M. Kim, J. J. Park, B. Lee, Y. J. Go, and S. W. Jung, "Efficient 1:N fingerprint matching algorithm using matching score distribution," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 18, no. 3, pp. 208-217, 2012. https://doi.org/10.5302/J.ICROS.2012.18.3.208