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A Big Survey on Biometrics for Human Identification

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Prognostic Models in Healthcare: AI and Statistical Approaches

Part of the book series: Studies in Big Data ((SBD,volume 109))

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Abstract

Biometrics are a branch of science that is used to identify as well as authenticate. Biometrics are basically of two types: behavioral biometrics and physiological biometrics. Characteristics and biometrics are fundamentally fixed and unique, allowing individuals to distinguish one from another. Biometric authentication systems have received more attention in recent years than other traditional authentication methods such as passwords or signatures. All human biological traits are unique as biometrics such as fingerprints, palms, irises, palm blood vessels and fingerprint blood vessels, and other biometrics. Biometric identification systems basically have a complex structure that consists of different parts. Biometric-based authentication systems and authentication methods, along with other authentication systems, can improve the security aspects of authentication systems. Identification methods and tools are used in many important and essential applications such as surveillance processes, security investigations, fraud detection technologies, and access controls. Biometric-based identification methods in machine learning consist mainly of preprocessing, feature extraction, feature selection, classification, and finally evaluation. These systems can also be based on one biometric or based on several biometrics together. In this chapter, we examine the methods of identifying identity information with the help of various biometrics, highlight the challenges in each biometrics, and introduce the solutions that have been proposed to overcome this challenge.

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Authors and Affiliations

  1. Department of Bioelectrics and Biomedical Engineering, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

    Zahra Karimi

  2. Department of Computer Engineering, Islamic Azad University, Najafabad Branch, Isfahan, Iran

    Somayeh Arab Najafabadi

  3. Department of Electrical Engineering, Isfahan University of Technology, Isfahan, Iran

    Aliakbar Rabbani Nezhad

  4. Department of Electrical Engineering, Tabriz University, Azerbaijan, Iran

    Farnaz Ahmadi

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  1. Zahra Karimi
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  2. Somayeh Arab Najafabadi
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  3. Aliakbar Rabbani Nezhad
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  4. Farnaz Ahmadi
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Correspondence to Zahra Karimi .

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  1. Artificial Intelligence and Data Analytics Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia

    Tanzila Saba

  2. Artificial Intelligence and Data Analytics Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia

    Amjad Rehman

  3. Artificial Intelligence and Data Science, Jio Institute, Ulwe, Navi Mumbai, India

    Sudipta Roy

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Karimi, Z., Najafabadi, S.A., Nezhad, A.R., Ahmadi, F. (2022). A Big Survey on Biometrics for Human Identification. In: Saba, T., Rehman, A., Roy, S. (eds) Prognostic Models in Healthcare: AI and Statistical Approaches. Studies in Big Data, vol 109. Springer, Singapore. https://doi.org/10.1007/978-981-19-2057-8_14

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