New Feature Extraction Approach Based on Adaptive Fuzzy Systems for Reliable Biometric Identification

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 753)

Abstract

Feature extraction for an optimal data representation is crucial for any biometric identification system. In this paper, we propose a new approach to extract the discriminant features within a biometric image in order to use Later in a biometric identification system. Thus, qualified as universal approximator, Takagi-Sugeno fuzzy system is adopted to model the biometric images through optimization of error target function, in which, a conjugate gradient method is used to establish the proposed algorithm. In order to evaluate our method, the PolyU multispectral palmprint database is used. The obtained results show that the biometric system errors are extremely reduced especially when the Blue spectral band is used. Thus, compared with the conventional features extraction methods, our method is more secure, fast and points at increased identification accuracy which will undoubtedly can be used in high secure applications.

Keywords

Biometric system Multispectral palmprint Takagi-Sugeno fuzzy system Conjugate gradient Data fusion 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Z. Tidjani
    • 1
  • A. Meraoumia
    • 2
  • S. Chitroub
    • 3
  • K. Ben sid
    • 1
  1. 1.Laboratoire de Génie Électrique (LAGE), Faculté des Nouvelles Technologies de l’Information et de la CommunicationUniversité Kasdi MerbahOuarglaAlgeria
  2. 2.LAboratory of Mathematics, Informatics and Systems (LAMIS)University of Larbi TebessiTebessaAlgeria
  3. 3.Laboratory of Intelligent and Communication Systems Engineering (LISIC), Electronics and Computer Science FacultyUSTHBBab EzzouarAlgeria

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