An Investigation of Face and Fingerprint Feature-Fusion Guidelines

  • Dane BrownEmail author
  • Karen Bradshaw
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 613)


There are a lack of multi-modal biometric fusion guidelines at the feature-level. This paper investigates face and fingerprint features in the form of their strengths and weaknesses. This serves as a set of guidelines to authors that are planning face and fingerprint feature-fusion applications or aim to extend this into a general framework. The proposed guidelines were applied to the face and fingerprint to achieve a 91.11 % recognition accuracy when using only a single training sample. Furthermore, an accuracy of 99.69 % was achieved when using five training samples.


Framework Face Fingerprint Feature-level Multi-modal biometrics 


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Computer ScienceRhodes UniversityGrahamstownSouth Africa
  2. 2.Council for Scientific and Industrial Research, Modelling and Digital SciencesPretoriaSouth Africa

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