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A comprehensive overview of feature representation for biometric recognition

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Abstract

The performance of any biometric recognition system heavily dependents on finding a good and suitable feature representation space where observations from different classes are well separated. Unfortunately, finding this proper representation is a challenging problem which has taken a huge interest in machine learning and computer vision communities. In the this paper we present a comprehensive overview of the different existing feature representation techniques. This is carried out by introducing simple and clear taxonomies as well as effective explanation of the prominent techniques. This is intended to guide the neophyte and provide researchers with state-of-the-art approaches in order to help advance the research topic in biometrics.

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Acknowledgments

This publication was made possible using a grant from the Qatar National Research Fund through National Priority Research Program (NPRP) # NPRP 8-140-2-065. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the Qatar National Research Fund or Qatar University.

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  1. Department of Computer Science and Engineering, Qatar University, Doha, Qatar

    Imad Rida, Noor Al-Maadeed & Somaya Al-Maadeed

  2. Department of Computer Science and Engineering, National Institute of Technology Rourkela, Rourkela, 769008, India

    Sambit Bakshi

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Rida, I., Al-Maadeed, N., Al-Maadeed, S. et al. A comprehensive overview of feature representation for biometric recognition. Multimed Tools Appl 79, 4867–4890 (2020). https://doi.org/10.1007/s11042-018-6808-5

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