Personal Recognition Using Single-Sensor Multimodal Hand Biometrics

  • Andreas Uhl
  • Peter Wild
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5099)


Single-sensor approaches to multimodal biometric authentication targeting the human hand in multiple-matcher scenarios provide higher security in terms of accuracy and resistance to biometric system attacks than unimodal systems. This paper introduces a novel multimodal hand biometric system using palmar images acquired by a commercially available flatbed scanner. Hence, the presented approach to personal recognition is independent of specific biometric sensors, such as fingerprint readers or palmprint scanners. Experimental results with a minimum half total error rate of 0.003% using a database of 443 hand images will illustrate the performance improvement when hand-geometry, fingerprint and palmprint-based features are combined.


Equal Error Rate Biometric System Hand Image Personal Recognition Palmprint Image 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Andreas Uhl
    • 1
  • Peter Wild
    • 1
  1. 1.Department of Computer SciencesUniversity of SalzburgSalzburgAustria

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