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Dominant Set Approach to ECG Biometrics

  • Andrè Lourenço
  • Samuel Rota Bulò
  • Carlos Carreiras
  • Hugo Silva
  • Ana L. N. Fred
  • Marcello Pelillo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8258)

Abstract

Electrocardiographic (ECG) signals are emerging as a recent trend in the field of biometrics. In this paper, we propose a novel ECG biometric system that combines clustering and classification methodologies. Our approach is based on dominant-set clustering, and provides a framework for outlier removal and template selection. It enhances the typical workflows, by making them better suited to new ECG acquisition paradigms that use fingers or hand palms, which lead to signals with lower signal to noise ratio, and more prone to noise artifacts. Preliminary results show the potential of the approach, helping to further validate the highly usable setups and ECG signals as a complementary biometric modality.

Keywords

Biometrics ECG Clustering Dominant Set Outlier Detection Template Selection 

References

  1. 1.
    Clifford, G.D.: ECG Statistics, Noise, Artifacts, and Missing Data. In: Clifford, G.D., Azuaje, F., Mcsharry, P. (eds.) Advanced Methods and Tools for ECG Data Analysis. Artech House Publishers (2006)Google Scholar
  2. 2.
    Biel, L., Petterson, O., Phillipson, L., Wide, P.: ECG analysis: A new approach in human identification. IEEE Trans. Inst. and Measurement 50(3), 808–812 (2001)CrossRefGoogle Scholar
  3. 3.
    Wang, Y., Agrafioti, F., Hatzinakos, D., Plataniotis, K.N.: Analysis of human electrocardiogram for biometric recognition. EURASIP J. Adv. S. Processing (2008)Google Scholar
  4. 4.
    Chan, A.D.C., Hamdy, M.M., Badre, A., Badee, V.: Wavelet distance measure for person identification using electrocardiograms. IEEE Trans. on Instrumentation and Measurement 57(2), 248–253 (2008)CrossRefGoogle Scholar
  5. 5.
    Odinaka, I., Lai, P.H., Kaplan, A., O’Sullivan, J., Sirevaag, E., Rohrbaugh, J.: ECG biometric recognition: A comparative analysis. IEEE Trans. on Information Forensics and Security 7(6), 1812–1824 (2012)CrossRefGoogle Scholar
  6. 6.
    Silva, H., Lourenço, A., Canento, F., Fred, A., Raposo, N.: ECG biometrics: Principles and applications. In: Proc. of the 6th Int’l Conf. on Bio-Inspired Systems and Signal Processing, BIOSIGNALS (2013)Google Scholar
  7. 7.
    Pavan, M., Pelillo, M.: Dominant sets and pairwise clustering. IEEE Trans. Pattern Analysis and Machine Intelligence 29(1), 167–172 (2007)CrossRefGoogle Scholar
  8. 8.
    Silva, H., Gamboa, H., Fred, A.: One lead ECG based personal identification with feature subspace ensembles. In: Perner, P. (ed.) MLDM 2007. LNCS (LNAI), vol. 4571, pp. 770–783. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  9. 9.
    Lourenço, A., Silva, H., Carreiras, C., Fred, A.: Outlier detection in non-intrusive ECG biometric system. In: Kamel, M., Campilho, A. (eds.) ICIAR 2013. LNCS, vol. 7950, pp. 43–52. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  10. 10.
    Lourenço, A., Silva, H., Fred, A.L.N.: ECG-based biometrics: A real time classification approach. In: IEEE Int’l W. Machine Learning for Signal Proc. (2012)Google Scholar
  11. 11.
    Torsello, A., Rota Bulò, S., Pelillo, M.: Grouping with asymmetric affinities: A game-theoretic perspective. In: IEEE Conf. Computer Vision and Patt. Recogn., pp. 292–299 (2006)Google Scholar
  12. 12.
    Rota Bulò, S., Pelillo, M.: A game-theoretic approach to hypergraph clustering. IEEE Trans. Patt. Analysis Machine Intell. 35(6), 1312–1327 (2013)CrossRefGoogle Scholar
  13. 13.
    Rota Bulò, S., Pelillo, M., Bomze, I.M.: Graph-based quadratic optimization: A fast evolutionary approach. Comp. Vis. and Image Understanding 115, 984–995 (2011)CrossRefGoogle Scholar
  14. 14.
    Kontschieder, P., Rota Bulò, S., Donoser, M., Pelillo, M., Bischof, H.: Evolutionary hough games for coherent object detection. Comp. Vis. and Image Understanding 116, 1149–1158 (2012)CrossRefGoogle Scholar
  15. 15.
    Uludag, U., Ross, A., Jain, A.: Biometric template selection and update: a case study in fingerprints. Pattern Recognition 37(7), 1533–1542 (2004)CrossRefGoogle Scholar
  16. 16.
    Liu, N., Wang, Y.: Template selection for on-line signature verification. In: Proc. of the 19th Int. Conf. on Pattern Recognition (ICPR), pp. 1–4 (December 2008)Google Scholar
  17. 17.
    Silva, H., Lourenço, A., Fred, A.L.N.: Finger ECG signal for user authentication: Usability and performance. In: IEEE BTAS (September 2013)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Andrè Lourenço
    • 1
    • 2
  • Samuel Rota Bulò
    • 3
  • Carlos Carreiras
    • 2
  • Hugo Silva
    • 2
  • Ana L. N. Fred
    • 2
  • Marcello Pelillo
    • 4
  1. 1.Instituto Superior de Engenharia de LisboaLisbonPortugal
  2. 2.Instituto de Telecomunicações, Instituto Superior TécnicoLisbonPortugal
  3. 3.FBK-irstTrentoItaly
  4. 4.DAISUniversitá Ca’ Foscari VeneziaVeniceItaly

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