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Multimodal Personal Authentication Using Iris and Knuckleprint

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Intelligent Computing Theory (ICIC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8588))

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Abstract

This paper proposes multi-modal authentication system by fusing iris and knuckleprint images. The iris and knuckleprint ROI’s are preprocessed using the proposed LGBP method to obtain robust features. The corners features are extracted and matched using the proposed CIOF dissimilarity measure. The proposed approach has been tested on publicly available CASIA 4.0 Interval and Lamp iris along with PolyU knuckleprint databases. It is also tested on multimodal databases that are created by fusing iris and knuckleprint and has shown encouraging results.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, 208016, India

    Aditya Nigam & Phalguni Gupta

Authors
  1. Aditya Nigam
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  2. Phalguni Gupta
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. Electrical and Electronics Department, Politecnico of Bari, Via Orabona, 4,, 70125, Bari, Italy

    Vitoantonio Bevilacqua

  3. School of Electrical, Computer and Telecommunications Engineering, University of Wollongon, 2522, North Wollongon, NSW, Australia

    Prashan Premaratne

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Nigam, A., Gupta, P. (2014). Multimodal Personal Authentication Using Iris and Knuckleprint. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theory. ICIC 2014. Lecture Notes in Computer Science, vol 8588. Springer, Cham. https://doi.org/10.1007/978-3-319-09333-8_90

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  • DOI: https://doi.org/10.1007/978-3-319-09333-8_90

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09332-1

  • Online ISBN: 978-3-319-09333-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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