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A Systematic Review on Physiological-Based Biometric Recognition Systems: Current and Future Trends

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Abstract

Biometric deals with the verification and identification of a person based on behavioural and physiological traits. This article presents recent advances in physiological-based biometric multimodalities, where we focused on finger vein, palm vein, fingerprint, face, lips, iris, and retina-based processing methods. The authors also evaluated the architecture, operational mode, and performance metrics of biometric technology. In this article, the authors summarize and study various traditional and deep learning-based physiological-based biometric modalities. An extensive review of biometric steps of multiple modalities by using different levels such as preprocessing, feature extraction, and classification, are presented in detail. Challenges and future trends of existing conventional and deep learning approaches are explained in detail to help the researcher. Moreover, traditional and deep learning methods of various physiological-based biometric systems are roughly analyzed to evaluate them. The comparison result and discussion section of this article indicate that there is still a need to develop a robust physiological-based method to advance and improve the performance of the biometric system.

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Acknowledgements

The work of this paper is financially supported by NSF of Guangdong Province (No. 2019A1515010833) and fundamental Research Funds for the Central Universities (No. 2020ZYGXZR089).

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  1. School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China

    Kashif Shaheed, Aihua Mao & Xingming Zhang

  2. Key Laboratory of Space Photoelectric Detection and Perception, Ministry of Industry and Information Technology and College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, Jiangsu, China

    Imran Qureshi

  3. Department of Computational Sciences, Maharaja Ranjit Singh Punjab Technical University, Bathinda, Punjab, 151001, India

    Munish Kumar

  4. College of Computer and Information Sciences, Imam Muhammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia

    Qaisar Abbas

  5. School of Software Engineering, Shandong University, Jinan, 250100, China

    Inam Ullah

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Shaheed, K., Mao, A., Qureshi, I. et al. A Systematic Review on Physiological-Based Biometric Recognition Systems: Current and Future Trends. Arch Computat Methods Eng 28, 4917–4960 (2021). https://doi.org/10.1007/s11831-021-09560-3

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