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Fingerprint Recognition Based on Adaptive Neuro-Fuzzy Inference System

  • Tripti Rani Borah
  • Kandarpa Kumar Sarma
  • Pran Hari Talukdar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8251)

Abstract

Fuzzy logic (FL) is a powerful problem solving methodology receiving wide spread acceptance for a range of applications. FL is also considered for image understanding applications such as edge detection, feature extraction, classification and clustering. It provides a simple and easy way to draw a definite conclusion from ambiguous, imprecise or vague information. Like Artificial Neural Network (ANN) models, some fuzzy inference system (FIS)s have the capability of universal approximation. The adaptive neuro-fuzzy inference system (ANFIS) belongs to the class of systems commonly known as neuro-fuzzy systems (NFs). NFs combines the advantages of ANN with those of fuzzy systems. An ANFIS based identification system is described here which uses fingerprint as an input. Experiments are carried out using a number of samples. Obtained results show that the system is reliable enough for considering it as a part of a verification mechanism.

Keywords

Root Mean Square Error Fuzzy Logic Fuzzy Inference System Fingerprint Image Fingerprint Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Jain, A., Hong, L., Pankanti, S.: Biometric Identification. Communications of the ACM 43(2), 91–98 (2000)CrossRefGoogle Scholar
  2. 2.
    Jain, A., Hong, L., Pankanti, S., Bolle, R.: An identity authentication system using fingerprints. Proceedings of the IEEE 85, 1365–1388 (1997)CrossRefGoogle Scholar
  3. 3.
    Thai, R.: Fingerprint Image Enhancement and Minutiae Extraction. B. Eng. thesis, The University of Western Australia (2003)Google Scholar
  4. 4.
    Ross, T.J.: Fuzzy logic with Engineering Applications, 2nd edn. Wiley India, New Delhi (2008)Google Scholar
  5. 5.
    Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition, 2nd edn. Springer Professional Computing, Berlin (2009)CrossRefGoogle Scholar
  6. 6.
    Borah, T.R., Sarma, K.K., Talukdar, P.H.: Fingerprint Recognition using Artificial Neural Network. International Journal of Electronics Signals and Systems (IJESS) 3(1), 98–101 (2013)Google Scholar
  7. 7.
    Jang, R.J.: ANFIS: Adaptive-Network Based Fuzzy Inference System. IEEE Transaction on Systems, Man and Cybernetics 23(3) (1993)Google Scholar
  8. 8.
    Hsieh, C.T., Hu, C.S.: An Application of Fuzzy Logic and Neural network to Fingerprint Recognition. In: Proceedings of IEEE-Eurasip Nonlinear Signal and Image Processing (NSIP 2005), Japan, vol. 20 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Tripti Rani Borah
    • 1
  • Kandarpa Kumar Sarma
    • 2
  • Pran Hari Talukdar
    • 3
  1. 1.Department of Computer ScienceGauhati University GuwahatiIndia
  2. 2.Dept. of Electronics and Communication TechnologyGauhati UniversityGuwahatiIndia
  3. 3.Department of Instrumentation and USICGauhati UniversityGuwahatiIndia

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