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Local Descriptor and Feature Selection Based Palmprint Recognition System

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Emerging Trends in Intelligent Computing and Informatics (IRICT 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1073))

Abstract

In this paper, we present a system based on a feature selection approach for solving the recognition problem in a multimodal biometric system combining both left and right palmprints of the same subject. In particular, the fusion of two or more traits, at feature-level, results in a long feature vector that needs large storage space, makes the execution time of the recognition task very long, and may include redundant and irrelevant features that can affect the recognition accuracy. To overcome these problems, feature selection is performed using genetic algorithms (GAs) and backtracking search algorithm for a comparison purpose. The experimental results show the usefulness of feature selection, especially the use of genetic algorithms, on the robustness of the multimodal biometric system as regards the feature vector length and run-time reduction, and the significant increase of the recognition rate.

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Author information

Authors and Affiliations

  1. RELA(CS)² Laboratory, University of Oum El-Bouaghi, 04000, Oum El-Bouaghi, Algeria

    Chérif Taouche

  2. NTIC Faculty, University of Constantine 2, 25016, Constantine, Algeria

    Chérif Taouche & Hacene Belhadef

Authors
  1. Chérif Taouche
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  2. Hacene Belhadef
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Corresponding author

Correspondence to Chérif Taouche .

Editor information

Editors and Affiliations

  1. College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia

    Faisal Saeed

  2. School of Computing, Universiti Utara Malaysia (UUM), Sintok, Kedah Darul Aman, Malaysia

    Fathey Mohammed

  3. Management of Information Systems Department College of Business Administration, Taibah University, Yanbu, Saudi Arabia

    Nadhmi Gazem

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Taouche, C., Belhadef, H. (2020). Local Descriptor and Feature Selection Based Palmprint Recognition System. In: Saeed, F., Mohammed, F., Gazem, N. (eds) Emerging Trends in Intelligent Computing and Informatics. IRICT 2019. Advances in Intelligent Systems and Computing, vol 1073. Springer, Cham. https://doi.org/10.1007/978-3-030-33582-3_72

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