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Impact of Some Biometric Modalities on Forensic Science

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Computational Intelligence in Digital Forensics: Forensic Investigation and Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 555))

Abstract

Recently, forensic science has had many challenges in many different types of crimes and crime scenes, vary from physical crimes to cyber or computer crimes. Accurate and efficient human identification or recognition have become crucial for forensic applications due to the large diversity of crime scenes, and because of the increasing need to accurately identify criminals from the available crime evidences. Biometrics is an emerging technology that provides accurate and highly secure personal identification and verification systems for civilian and forensic applications. The positive impact of biometric modalities on forensic science began with the rapid developments in computer science, computational intelligence, and computing approaches. These advancements have been reflected in the biometric modality capturing process, feature extraction, feature robustness, and features matching. A complete and automatic biometric identification or recognition systems have been built accordingly. This chapter presents a study of the impacts of using some biometric modalities in forensic applications. Although biometrics identification replaces human work with computerized and automatic systems in order to achieve better performance, new challenges have arisen. These challenges lie in biometric system reliability and accuracy, system response time, data mining and classification, and protecting user privacy. This chapter sheds light on the positive and the negative impacts of using some biometric modalities in forensic science. In particular, the impacts of fingerprint image, facial image, and iris patterns are considered. The selected modalities are covered preliminarily before tackling their impact on forensic applications. Furthermore, an extensive look at the future of biometric modalities deployment in forensic applications is covered as the last part of the chapter.

An erratum for this chapter can be found at http://dx.doi.org/10.1007/978-3-319-05885-6_19

An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-3-319-05885-6_19

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Author information

Authors and Affiliations

  1. Faculty of Engineering, Member of the Scientific Research Group in Egypt (SRGE), Al Azhar University, Qena, Egypt

    Ali Ismail Awad

  2. Faculty of Computers & Information, Chairman of Scientific Research Group in Egypt (SRGE), Cairo University, Cairo, Egypt

    Aboul Ella Hassanien

Authors
  1. Ali Ismail Awad
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  2. Aboul Ella Hassanien
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Correspondence to Ali Ismail Awad .

Editor information

Editors and Affiliations

  1. Department of Software Engineering Faculty of Information and, Technical University of Malaysia Melaka (UTeM), Durian Tunggal, Malaysia

    Azah Kamilah Muda

  2. Department of Software Engineering Faculty of Info. and Comm. Tech., Technical University of Malaysia Melaka (UTeM), Durian Tunggal, Malaysia

    Yun-Huoy Choo

  3. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, Washington, Washington, USA

    Ajith Abraham

  4. Dept. of Computer Sci. and Engineering Center of Excellence for Document, The State University of New York SUNY, Buffalo, New York, USA

    Sargur N. Srihari

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Awad, A.I., Hassanien, A.E. (2014). Impact of Some Biometric Modalities on Forensic Science. In: Muda, A., Choo, YH., Abraham, A., N. Srihari, S. (eds) Computational Intelligence in Digital Forensics: Forensic Investigation and Applications. Studies in Computational Intelligence, vol 555. Springer, Cham. https://doi.org/10.1007/978-3-319-05885-6_3

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  • DOI: https://doi.org/10.1007/978-3-319-05885-6_3

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05884-9

  • Online ISBN: 978-3-319-05885-6

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