Acoustic Ear Recognition

  • Ton H. M. Akkermans
  • Tom A. M. Kevenaar
  • Daniel W. E. Schobben
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3832)


We investigate how the acoustic properties of the pinna – i.e. the outer flap of the ear- and the ear canal can be used as a biometric. The acoustic properties can be measured relatively easy with an inexpensive sensor and feature vectors can be derived with little effort. Classification results for three platforms are given (headphone, earphone, mobile phone) using noise as an input signal. Furthermore, preliminary results are given for the mobile phone platform where we use music as an input signal. We achieve equal error rates in the order of 1%-5%, depending on the platform that is used to do the measurement.


Feature Vector Mobile Phone Linear Discriminant Analysis Acoustic Property Excitation Signal 
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.


  1. 1.
    Sandia Corporation, patent US 5,787,187, Systems and methods for biometric identification using the acoustic properties of the ear canalGoogle Scholar
  2. 2.
    Moreno, B., Sanchez, A., Velez, J.F.: On the use of outer ear images for personal identification in security applications. In: Proceedings. IEEE 33rd Annual 1999 International Carnahan Conference on Security Technology, October 5-7, pp. 469–476 (1999)Google Scholar
  3. 3.
    Burge, M., Burger, W.: Ear biometrics in computer vision. In: Proc. 15th International Conference on Pattern Recognition, September 3-7, vol. 2, pp. 822–826 (2000)Google Scholar
  4. 4.
    Pun, K.H., Moon, Y.S.: Recent advances in ear biometrics. In: Proc. Sixth IEEE International Conference on Automatic Face and Gesture Recognition, May 17-19, pp. 164–169 (2004)Google Scholar
  5. 5.
    Tao, Y., Tew, A.I., Porter, S.J.: The Differential Pressure Synthesis Method for Estimating Acoustic Pressures on Human Heads. In: 112th Audio Engineering Society Convention, Munich, Germany, May 10–13 (2002)Google Scholar
  6. 6.
    Tuyls, P., Verbitskiy, E., Ignatenko, T., Schobben, D., Akkermans, T.: Privacy Protected Biometric Templates:Acoustic Ear Identification. Proc.SPIE 5404, 176–182 (2004)CrossRefGoogle Scholar
  7. 7.
    Linnartz, J.-P., Tuyls, P.: New shielding functions to enhance privacy and prevent misuse of biometric templates. In: Kittler, J., Nixon, M.S. (eds.) AVBPA 2003. LNCS, vol. 2688, pp. 393–402. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  8. 8.
    Tuyls, P., Goseling, J.: Capacity and Examples of Template Protection in Biometric Authentication systems. In: Maltoni, D., Jain, A.K. (eds.) BioAW 2004. LNCS, vol. 3087, pp. 158–170. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  9. 9.
    Tuyls, P., Akkermans, A., Kevenaar, T., Schrijen, G.-J., Bazen, A., Veldhuis, R.: Practical Biometric Authentication with Template Protection. In: Kanade, T., Jain, A., Ratha, N.K. (eds.) AVBPA 2005. LNCS, vol. 3546, pp. 436–446. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  10. 10.
    Akkermans, A.H.M., Kevenaar, T.A.M., Schobben, D.W.E.: Acoustic Ear Recognition for Person Identification. In: Accepted for the IEEE AutoID Workshop, Buffalo, New York, USA, October 17-18 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Ton H. M. Akkermans
    • 1
  • Tom A. M. Kevenaar
    • 1
  • Daniel W. E. Schobben
    • 1
  1. 1.Philips ResearchEindhovenThe Netherlands

Personalised recommendations