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)


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.


Biometrics ECG Clustering Dominant Set Outlier Detection Template Selection 


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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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