A New Personal Verification Technique Using Finger-Knuckle Imaging

  • Rafal DorozEmail author
  • Krzysztof Wrobel
  • Piotr Porwik
  • Hossein Safaverdi
  • Michal Senejko
  • Janusz Jezewski
  • Pawel Popielski
  • Slawomir Wilczynski
  • Robert Koprowski
  • Zygmunt Wrobel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9876)


This paper focuses on automatic pattern-based extracting of biometric features where finger-knuckle images are analyzed. Knuckle images are captured by digital camera, and then by the image processing techniques the most relevant features (patterns) are discovered and extracted. Knuckle-based images were filtered by the Hessian filters. It enabled to enhance image regions with image ridges. In the next stage similarity of images were computed by the Normalized Cross-Correlation algorithm. Ultimately, similarities were classified by the k-NN classifier. The discovered features belong to so-called human physical features, which involves innate human characteristics. Physical biometric features can often be gathered with specialized hardware, needing only software for analysis. That capacity makes such biometrics simpler.

We conducted a variety of experiments and showed advantages and disadvantages of the approaches with promising results.


Biometrics Finger-Knuckle imaging Cross-correlation k-NN 


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Rafal Doroz
    • 1
    Email author
  • Krzysztof Wrobel
    • 1
  • Piotr Porwik
    • 1
  • Hossein Safaverdi
    • 1
  • Michal Senejko
    • 1
  • Janusz Jezewski
    • 2
  • Pawel Popielski
    • 1
  • Slawomir Wilczynski
    • 3
  • Robert Koprowski
    • 1
  • Zygmunt Wrobel
    • 1
  1. 1.Institute of Computer ScienceUniversity of SilesiaSosnowiecPoland
  2. 2.Institute of Medical Technology and Equipment (ITAM)ZabrzePoland
  3. 3.Department of Basic Biomedical ScienceMedical University of SilesiaSosnowiecPoland

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