Score Level Fusion Scheme in Hybrid Multibiometric System

  • Saliha Artabaz
  • Layth SlimanEmail author
  • Karima Benatchba
  • Hachemi Nabil Dellys
  • Mouloud Koudil
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9429)


Multibiometric systems are a promising area that addresses a number of unimodal biometric systems drawbacks. The main limit of these systems is the lack of information in terms of quantity (number of discriminant features) and quality (diversity of information, correlation…). Using multiple sources of information and/or treatment is a solution to overcome these problems and enhance system performances. Performance requirements of current systems related to context use involve designed solutions that optimally satisfy security requirements. This can represent an optimization problem that aims at searching the optimal solution matching security needs. In our study, we are interested in combining different score level rules using an evolutionary algorithm. We use Genetic Algorithm to derive a score fusion function based on primitive operations. The process uses an optimized tree to determine function structure. We perform experiments on the XM2VTS score database based on a well-founded protocol for reliable results. The obtained results are promising and outperforms other fusion rules.


Score level fusion Multibiometric Genetic algorithm Tree representation 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Saliha Artabaz
    • 1
  • Layth Sliman
    • 2
    Email author
  • Karima Benatchba
    • 1
  • Hachemi Nabil Dellys
    • 1
  • Mouloud Koudil
    • 1
  1. 1.Ecole nationale Supérieure d’Informatique ESIOued-Smar, AlgerAlgeria
  2. 2.Ecole d’ingénieur généraliste en informatique et technologies du numérique EfreiVillejuif, ParisFrance

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