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Iris Biometrics Recognition in Security Management

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Enterprise Security (ES 2015)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10131))

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Abstract

Application of iris recognition for human identification has significant potential for developing a robust identification system. This is due to the fact that iris pattern of individuals are unique, differentiable from left to right eye and is almost stable over the time. However, performance of the existing iris recognition systems depends on the signal processing algorithms they use for iris segmentation, feature extraction and template matching. Like any other signal processing system, the performance of the iris recognition system is depend on the existing level of noise in the image and can be deteriorated as the level of noise increases. The building block of the iris recognition systems, techniques to mitigate the effect of the noise in each stages, criteria to assess the performance of different iris recognition techniques and publicly available iris datasets are discussed in this chapter.

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Authors and Affiliations

  1. School of Computing, Creative Technologies and Engineering, Leeds Beckett University, Leeds, UK

    Ahmad Ghaffari, Amin Hosseinian-Far & Akbar Sheikh-Akbari

Authors
  1. Ahmad Ghaffari
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  2. Amin Hosseinian-Far
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  3. Akbar Sheikh-Akbari
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Corresponding author

Correspondence to Ahmad Ghaffari .

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Editors and Affiliations

  1. Xi’an Jiaotong-Liverpool University, Suzhou, China

    Victor Chang

  2. School of Computing, Creative Technologies, and Engineering, Leeds Beckett University, Leeds, United Kingdom

    Muthu Ramachandran

  3. University of Southampton , Southampton, United Kingdom

    Robert J. Walters

  4. Department of Electronics and Computer Science, University of Southampton, Southampton, United Kingdom

    Gary Wills

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Ghaffari, A., Hosseinian-Far, A., Sheikh-Akbari, A. (2017). Iris Biometrics Recognition in Security Management. In: Chang, V., Ramachandran, M., Walters, R., Wills, G. (eds) Enterprise Security. ES 2015. Lecture Notes in Computer Science(), vol 10131. Springer, Cham. https://doi.org/10.1007/978-3-319-54380-2_4

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  • DOI: https://doi.org/10.1007/978-3-319-54380-2_4

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