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Robustness of Biometrics by Image Processing Technology

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Robust Image Authentication in the Presence of Noise

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Abstract

Feature extraction is the most critical part of biometric authentication systems. The majority of biometric systems proposed in the last years are using alignment to ensure robust authentication in the presence of affine transformations like rotation and translation. Nevertheless, alignment is time consuming, and misalignment leads to the lack of accuracy. Using template-protection, there is a need for additional information to perform explicit alignment. It is therefore not clear whether this information could be used to attack the protected biometric template. This Chapter presents a comparative view on alignment-free features for biometric authentication from the perspective of pattern recognition and digital image processing as well as biometrics. The basics of these disciplines are aggregated and different proposed techniques are described, assessed and compared. Finally, an evaluation strategy from the field of digital image processing is applied to biometrics in order to assess robustness and invariance of feature extraction in biometrics.

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Authors and Affiliations

  1. Chair for Data Communications Systems, University of Siegen, 57076, Siegen, Germany

    Robin Fay & Christoph Ruland

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  1. Robin Fay
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  2. Christoph Ruland
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Correspondence to Robin Fay .

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  1. University of Siegen, Siegen, Germany

    Nataša Živić

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Fay, R., Ruland, C. (2015). Robustness of Biometrics by Image Processing Technology. In: Živić, N. (eds) Robust Image Authentication in the Presence of Noise. Springer, Cham. https://doi.org/10.1007/978-3-319-13156-6_6

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  • DOI: https://doi.org/10.1007/978-3-319-13156-6_6

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