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Fingerprint Classification

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Orthogonal Image Moments for Human-Centric Visual Pattern Recognition

Part of the book series: Cognitive Intelligence and Robotics ((CIR))

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Abstract

Fingerprints are the impression of minute ridges and valleys that are found on the fingertips of every person. Among all the biometric signatures, fingerprint maintains one of the highest levels of accuracy, reliability, and consistency, and hence has been extensively used for identifying individuals.

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Author information

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh

    S. M. Mahbubur Rahman

  2. Institute of Statistical Research and Training, University of Dhaka, Dhaka, Bangladesh

    Tamanna Howlader

  3. Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada

    Dimitrios Hatzinakos

Authors
  1. S. M. Mahbubur Rahman
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  2. Tamanna Howlader
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  3. Dimitrios Hatzinakos
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Corresponding author

Correspondence to S. M. Mahbubur Rahman .

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Rahman, S.M.M., Howlader, T., Hatzinakos, D. (2019). Fingerprint Classification. In: Orthogonal Image Moments for Human-Centric Visual Pattern Recognition. Cognitive Intelligence and Robotics. Springer, Singapore. https://doi.org/10.1007/978-981-32-9945-0_5

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  • DOI: https://doi.org/10.1007/978-981-32-9945-0_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-32-9944-3

  • Online ISBN: 978-981-32-9945-0

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