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Segmentation and Enhancement of Fingerprint Images Based on Automatic Threshold Calculations

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Book cover Recent Trends in Information and Communication Technology (IRICT 2017)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 5))

Abstract

A new approach to fingerprint image segmentation and feature extraction is proposed to improve the implementation of Automated Fingerprint Identification System (AFIS) based on automatic threshold values. The process starts by partitioning the fingerprint image manually into 16 × 16 pixels blocks. For each block, a local threshold is calculated using its mean, variance and coherence. Then, statistical analysis is performed to find the optimal threshold value for each block. This threshold is then used to extract a foreground of the fingerprint image from the background. Later, the foreground is enhanced using a newly developed technique called filling-in-the-gap process to fill in the gaps in the foreground and eliminate any unwanted handwritten annotations in the image. The current method was evaluated using the NIST-14 database and showed reliable results on different quality images.

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Author information

Authors and Affiliations

  1. Faculty of Business Informatics, University of Information Technology and Communications (UOITC), Baghdad, Iraq

    Alaa Ahmed Abbood & Atheer Akram Abdul Razzaq

  2. Faculty of Computing, UTM-IRDA Digital Media Centre (MaGIC-X), University Technology Malaysia, 81310, Skudai, Johor Bahru, Malaysia

    Ghazali Sulong

  3. College of Education, Florida State University, Tallahassee, FL, 32306, USA

    Sabine U. Peters

Authors
  1. Alaa Ahmed Abbood
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  2. Ghazali Sulong
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  3. Atheer Akram Abdul Razzaq
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  4. Sabine U. Peters
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Corresponding author

Correspondence to Alaa Ahmed Abbood .

Editor information

Editors and Affiliations

  1. Faculty of Computing Information Systems Department, Universiti Teknologi Malaysia, Johar, Skudai, Malaysia

    Faisal Saeed

  2. Faculty of Computing Information Systems Department, Universiti Teknologi Malaysia, Johar, Skudai, Malaysia

    Nadhmi Gazem

  3. Department of Computer Science and Engineering, SOA University, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  4. Faculty of Computing, ISSI Research Lab, University of Technology Malaysia, Skudai, Malaysia

    Ali Saleh Saed Balaid

  5. Faculty of Computing, University of Technology Malaysia, Skudai, Malaysia

    Fathey Mohammed

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Abbood, A.A., Sulong, G., Razzaq, A.A.A., Peters, S.U. (2018). Segmentation and Enhancement of Fingerprint Images Based on Automatic Threshold Calculations. In: Saeed, F., Gazem, N., Patnaik, S., Saed Balaid, A., Mohammed, F. (eds) Recent Trends in Information and Communication Technology. IRICT 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-59427-9_43

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  • DOI: https://doi.org/10.1007/978-3-319-59427-9_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59426-2

  • Online ISBN: 978-3-319-59427-9

  • eBook Packages: EngineeringEngineering (R0)

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