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Soft Computing Applications pp 891–902Cite as

Fast Fingerprint Orientation Field Estimation Incorporating General Purpose GPU

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 357))

Abstract

Fingerprint is one of the broadly utilized biometric traits for personal identification in both civilian and forensic applications due to its high acceptability, strong security, and low cost. Fingerprint ridge orientation is one of the global fingerprint representations that keeps the holistic ridge structure in a small storage area. The importance of fingerprint ridge orientation comes from its usage in fingerprint singular point detection, coarse level classification, and fingerprint alignment. However, processing time is an important factor in any automatic fingerprint identification system, estimating that ridge orientation image may consume long processing time. This research presents an efficient ridge orientation estimation approach by incorporating a Graphics Processing Unit (GPU) capability to the traditional pixel gradient method. The simulation work shows a significant enhancement in ridge orientation estimation time by 6.41x using a general purpose GPU in comparison to the CPU execution.

An erratum of this chapter can be found under DOI 10.1007/978-3-319-18416-6_110

An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-3-319-18416-6_110

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Author information

Authors and Affiliations

  1. Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, Luleå, Sweden

    Ali Ismail Awad

  2. Faculty of Engineering, Luleå University of Technology, Luleå, Sweden

    Ali Ismail Awad

Authors
  1. Ali Ismail Awad
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Correspondence to Ali Ismail Awad .

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Editors and Affiliations

  1. Department of Automation and Applied Informatics, Aurel Vlaicu University of Arad Faculty of Engineering, Arad, Romania

    Valentina Emilia Balas

  2. Faculty of Science and Technology, Data Science Institute, Bournemouth University, Poole, United Kingdom

    Lakhmi C. Jain

  3. University of Belgrade, Belgrade, Serbia

    Branko Kovačević

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Awad, A.I. (2016). Fast Fingerprint Orientation Field Estimation Incorporating General Purpose GPU. In: Balas, V., Jain, L., Kovačević, B. (eds) Soft Computing Applications. Advances in Intelligent Systems and Computing, vol 357. Springer, Cham. https://doi.org/10.1007/978-3-319-18416-6_70

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  • DOI: https://doi.org/10.1007/978-3-319-18416-6_70

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18415-9

  • Online ISBN: 978-3-319-18416-6

  • eBook Packages: EngineeringEngineering (R0)

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