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Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012 pp 1015–1023Cite as

Iris Recognition System Using Local Features Matching Technique

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 236))

Abstract

Iris is one of the most trustworthy biometric traits due to its stability and randomness. In this paper, the Iris Recognition System is developed with the intention of verifying both the uniqueness and performance of the human iris, as it is a briskly escalating way of biometric authentication of an individual. The proposed algorithm consists of an automatic segmentation system that is based on the Hough transform, and can localize the circular iris and pupil region, occluding eyelids and eyelashes, and reflections. The extracted iris region is then normalized into a rectangular block. Further, the texture features of normalized image are extracted using LBP (Local Binary Patterns). Finally, the Euclidean distance is employed for the matching process. In this thesis, the proposed system is tested with the co-operative database such as CASIA. With CASIA database, the recognition rate of proposed method is almost 91 %, which shows the iris recognition system is reliable and accurate biometric technology.

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Authors and Affiliations

  1. Department of Computer Science, Punjabi University, Patiala, India

    Alamdeep Singh & Amandeep Kaur

Authors
  1. Alamdeep Singh
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  2. Amandeep Kaur
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Corresponding author

Correspondence to Alamdeep Singh .

Editor information

Editors and Affiliations

  1. Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, Rajasthan, India

    B. V. Babu

  2. Department of Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya Nagar

  3. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Kusum Deep

  4. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, India

    Millie Pant

  5. Department of Applied Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

  6. Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, Rajasthan, India

    Kanad Ray

  7. Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, Rajasthan, India

    Umesh Gupta

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Singh, A., Kaur, A. (2014). Iris Recognition System Using Local Features Matching Technique. In: Babu, B., et al. Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012. Advances in Intelligent Systems and Computing, vol 236. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1602-5_107

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  • DOI: https://doi.org/10.1007/978-81-322-1602-5_107

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1601-8

  • Online ISBN: 978-81-322-1602-5

  • eBook Packages: EngineeringEngineering (R0)

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