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Data management for fingerprint recognition algorithm based on characteristic points' group

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper authors present data management solutions for new fingerprint recognition based on minutes groups. They compared existing fingerprint recognition data store methods and their own solutions. Authors proposed a new algorithm based on distribution minutiae' groups using selective attention algorithms.
Rocznik
Strony
123--130
Opis fizyczny
Bibliogr. 20 poz., tab., fig.
Twórcy
  • Wrocław University of Technology, Institute of Informatics, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland
autor
  • Wrocław University of Technology, Institute of Informatics, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland
Bibliografia
  • [1] Bazen A.M., Gerez S.H. (2003) Fingerprint matching by thinplate spline modelling of elastic deformations, Pattern Recognition.
  • [2] Bebis G., Deaconu T., Georgiopoulos M. (1999) Fingerprint Identification Using Delaunay Triangulation, IEEE ICIIS: 452-459.
  • [3] Cappelli R., Lumini A., D. Maio and D. Maltoni (1999) Fingerprint Classification by Directional Image Partitioning, IEEE Transactions on Pattern Analysis MachineIntelligence, vol.21, no. 5:402-421
  • [4] Chikkerur S., Govindaraju V., Cartwright E. N.(2006) K-plet and coupled bfs: A graph based fingerprint representation and matching algorithm. LNCS: 309-315.
  • [5] Grzeszyk C. (1992) Forensic fingerprint examination marks. (in Polish), Wydawnictwo Centrum Szkolenia Policji, Legionowo.
  • [6] He Y., Ou Z.(2005) Fingerprint matching algorithm based on local minutiae adjacency graph, Journal of Harbin Institute of Technology 10/05, pp. 95-103.
  • [7] Huk M., Szczepanik M. (2011) Multiple classifier error probability for multi-class problems. Maintenance and Reliability 3: 12-17.
  • [8] Hicklin A., Watson C. Ulery B. (2005) How many people have fingerprints that are hard to match, NIST Interagency Report 7271.
  • [9] Hong L., Wan Y., Jain A. K. (1998) Fingerprint image enhancement: Algorithm and performance evaluation, IEEE Transactions on Pattern Analysis and Machine Intelligence:777-789
  • [10] Indovina M., Uludag U., Snelick R., Mink A., Jain A. (2003) Multimodal Biometric Authentication Methods: A COTS Approach, Proc. MMUA.
  • [11] Jain A. K., Ross A., Nandakumar K. (2011). Introducing to biometrics, Spinger.
  • [12] Maltoni D., Maio D., Jain A.K., Prabhakar S. (2009) Handbook of Fingerprint Recognition, 2nd Edition, Springer.
  • [13] Pankanti S, Prabhakar S., Jain A.K. (2001) On the individuality of fingerprints, Proceedings of Computer Vision and Pattern Recognition (CVPR).
  • [14] Parziale G., Niel A. (2004) A fingerprint matching using minutiae triangulation. Proc. of ICBA.
  • [15] Ratha N. K., Govindaraju V. (2007) Advances in Biometrics: Sensors, Algorithms andSystems, Springer.
  • [16] Ross A., Dass S.C., Jain A.K. (2005) A deformable model for fingerprint matching, Pattern Recognition 38(1): 95-103.
  • [17] Ross, A., Nandakumar K., Jain, A.K. (2011) Handbook of Multibiometrics (International Series on Biometrics), Springer.
  • [18] Shimooka T., Shimizu K. 2004. Artificial Immune System for Personal Identificationwith Finger Vein Pattern, Springer.
  • [19] Szczepanik M., Szewczyk R. (2008) Fingerprint identification algorithm (in Polish). KNS, vol. 1: 131-136.
  • [20] Wayman J.L., Jain A.K., Maltoni D., Maio D. (2005) Biometric Systems. Technology, Design and Performance Evaluation, 1st Edition, Springer.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a51e889d-88a7-40a2-8b88-4287fbba9812
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