Robustness of Biometrics by Image Processing Technology



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.


Feature Extraction Method Equal Error Rate Biometric System Invariant Moment Biometric Template 
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 International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Chair for Data Communications SystemsUniversity of SiegenSiegenGermany

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