Artificial Neural Network Based Automatic Face Model Generation System from Only One Fingerprint

  • Seref Sagiroglu
  • Necla Ozkaya
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5064)

Abstract

Biometrics technology has received increasingly more attention during the last three decades. Since the performance of biometric systems has reached a satisfactory level for applications, a number of biometric features have been deeply studied, tested and successfully deployed in applications. Relationships among biometric features have not been studied so far. This study focuses on analysing the existence of any relationships among fingerprints and faces. For doing that an intelligent system based on artificial neural networks for generating face models including eyes, nose, mouth, ears andface border from only one fingerprint with the errors among 2.0-12.9 % was developed. Experimental results have shown that there are close realitionships among fingerprints and faces and it is possible to generate faces from only one fingerprint image without knowing any information about faces. Although the proposed system is an initial study and it is still under development, the results are very encouraging and promising for the future developments and applications.

Keywords

Biometrics artificial neural network intelligent systems fingerprint identification face recognition 

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References

  1. 1.
    Maio, D., Maltoni, D., Jain, A.K., Prabhakar, S.: Handbook of fingerprint recognition. Springer, New York (2003)MATHGoogle Scholar
  2. 2.
    Jain, L.C., Halici, U., Hayashi, I., Lee, S.B., Tsutsui, S.: Intelligent biometric techniques in fingerprint and face recognition. CRC press, New York (1999) Google Scholar
  3. 3.
    Jain, A.K., Ross, A., Prabhakar, S.: An introduction to biometric recognition. IEEE Trans. on Circuits and Systems for Video Technology 14(1), 4–19 (2004)CrossRefGoogle Scholar
  4. 4.
    Jain, A.K., Ross, A., Pankanti, S.: Biometrics: a tool for information security. IEEE Trans. on Information Forensics and Security, 1(2), 125–143 (2006)CrossRefGoogle Scholar
  5. 5.
    Jain, A.K., Hong, L., Pankanti, S., Bolle, R.: An identity authentication system using fingerprints. Proceedings of the IEEE 85(9), 1365–1388 (1997)CrossRefGoogle Scholar
  6. 6.
    Jain, A.K., Pankanti, S., Prabhakar, S., Hong, L., Ross, A., Wayman, J.L.: Biometrics: A Grand Challenge. In: Proceedings of the Int. Conf. on Pattern Recognition, Cambridge, UK, August, vol. II, pp. 935–942 (2004)Google Scholar
  7. 7.
    Kovács-Vajna, Z.M.: A fingerprint verification system based on triangular matching and dynamic time warping. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1266–1276 (2000)CrossRefGoogle Scholar
  8. 8.
    Lumini, A., Nanni, L.: Two-class Fingerprint matcher. Pattern Recognition 39(4), 714–716 (2006)CrossRefMATHGoogle Scholar
  9. 9.
    Hong, L., Jain, A.: Integrating faces and fingerprints for personal identification. IEEE Trans. Pattern Analysis and Machine Intelligence 20(12), 1295–1307 (1998)CrossRefGoogle Scholar
  10. 10.
    Jain, A.K., Hong, L., Bolle, R.: On-line fingerprint verification. IEEE Trans. on Pattern Analysis and Machine Intelligence 19(4), 302–314 (1997)CrossRefGoogle Scholar
  11. 11.
    Zhou, J., Gu, J.: Modeling orientation fields of fingerprints with rational complex functions. Pattern Recognition 37(2), 389–391 (2004)CrossRefMathSciNetMATHGoogle Scholar
  12. 12.
    Hsieh, C.T., Lu, Z.Y., Li, T.C., Mei, K.C.: An Effective Method To Extract Fingerprint Singular Point. In: The Fourth Int. Conf./Exhibition on High Performance Computing in the Asia-Pacific Region, pp. 696–699 (2000)Google Scholar
  13. 13.
    Rämö, P., Tico, M., Onnia, V., Saarinen, J.: Optimized singular point detection algorithm for fingerprint images. In: Int. Conf. on Image Processing, pp. 242–245 (2001)Google Scholar
  14. 14.
    Zhang, Q., Yan, H.: Fingerprint classification based on extraction and analysis of singularities and pseudo ridges. Pattern Recognition 11, 2233–2243 (2004)Google Scholar
  15. 15.
    Wang, X., Li, J., Niu, Y.: Definition and extraction of stable points from fingerprint images. Pattern Recognition 40(6), 1804–1815 (2007)CrossRefMATHGoogle Scholar
  16. 16.
    Li, J., Yau, W.Y., Wang, H.: Combining singular points and orientation image information for fingerprint classification. Pattern Recognition 41(1), 353–366 (2008)CrossRefMATHGoogle Scholar
  17. 17.
    Kawagoe, M., Tojo, A.: Fingerprint pattern classification. Pattern Recognition 17(3), 295–303 (1984)CrossRefGoogle Scholar
  18. 18.
    Nilsson, K., Bigun, J.: Localization of corresponding points in fingerprints by complex filtering. Pattern Recognition Lett. 24, 2135–2144 (2003)CrossRefGoogle Scholar
  19. 19.
    Ozkaya, N., Sagiroglu, S., Wani, A.: An intelligent automatic fingerprint recognition system design. In: 5th Int. Conf. on Machine Learning and App., pp. 231–238 (2006)Google Scholar
  20. 20.
    Ross, A., Jain, A.K., Reisman, J.: A Hybrid Fingerprint Matcher. Pattern Recognition 36(7), 1661–1673 (2003)CrossRefGoogle Scholar
  21. 21.
    Cevikalp, H., Neamtu, M., Wilkes, M., Barkana, A.: Discriminative common vectors for face recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence 27(1), 4–13 (2005)CrossRefGoogle Scholar
  22. 22.
    Bouchaffra, D., Amira, A.: Structural Hidden Markov Models for Biometrics: Fusion of Face and Fingerprint. Special Issue of Pattern Recognition Journal, Feature Extraction and Machine Learning for Robust Multimodal Biometrics (Article in press, 2007) (available online)Google Scholar
  23. 23.
    Li, S.Z., Jain, A.K.: Handbook of Face Recognition. Springer, NewYork (2004)Google Scholar
  24. 24.
    Yang, M.H., Kriegman, D.J., Ahuja, N.: Detecting faces in images: a survey. IEEE Trans. on Pattern Analysis and Machine Intelligence 1(24), 34–58 (2002)CrossRefGoogle Scholar
  25. 25.
    Zhao, W., Chellappa, R., Phillips, P.J., Rosenfeld, A.: Face recognition: a literature survey. ACM Computing Surveys 35, 399–459 (2003)CrossRefGoogle Scholar
  26. 26.
    Haykin, S.: Neural Networks: A Comprehensive Foundation. Macmillan College Publishing Company, New York (1994)MATHGoogle Scholar
  27. 27.
    Sagiroglu, S., Beşdok, E., Erler, M.: Artificial intelligence applications in Engineering I: artificial neural networks. Ufuk publishing, Kayseri, Turkey (2003)Google Scholar
  28. 28.
    Sagar, V.K., Beng, K.J.A.: Hybrid Fuzzy Logic And Neural Network Model For Fingerprint Minutiae Extraction. In: Int. Conf. on Neural Netw., pp. 3255–3259 (1999)Google Scholar
  29. 29.
    Nagaty, K.A.: Fingerprints classification using artificial neural networks: a combined structural and statistical approach. Neural Networks 14, 1293–1305 (2001)CrossRefGoogle Scholar
  30. 30.
    Maio, D., Maltoni, D.: Neural network based minutiae filtering in fingerprints. In: 14th Int. Conf. on Pattern Recognition, pp. 1654–1658 (1998)Google Scholar
  31. 31.
    The Mathworks, Accelerating the Pace of Engineering and Science (2008), http://www.mathworks.com/access/helpdesk/help/toolbox/nnet/nnet.html?/access/helpdesk/help/toolbox
  32. 32.
    Moller, M.F.: A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning. Neurall Networks 6, 525–533 (1993)CrossRefGoogle Scholar
  33. 33.
    Novobilski, A., Kamangar, F.A.: Absolute percent error based fitness functions for evolving forecast models. In: FLAIRS Conf., pp. 591–595 (2001)Google Scholar
  34. 34.
    Biometrical and Artificial intelligence Technologies (2008), http://www.neurotechnologija.com/vf_sdk.html
  35. 35.
    Cox, I.J., Ghosn, J., Yianilos, P.N.: Feature-Based Face Recognition Using Mixture Distance. Computer Vision and Pattern Recognition, 209–216 (1996)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Seref Sagiroglu
    • 1
  • Necla Ozkaya
    • 2
  1. 1.Engineering and Architecture Faculty, Computer Engineering DepartmentGazi UniversityAnkaraTurkey
  2. 2.Engineering Faculty, Computer Engineering DepartmentErciyes UniversityKayseriTurkey

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