Identifying Three-Dimensional Palmprints With Modified Four-Patch Local Binary Pattern (MFPLBP)

Authors

  • Musab Tahseen Salahaldeen Al-Kaltakchi College of Engineering, Mustansiriyah University, Baghdad https://orcid.org/0000-0001-5542-9144
  • Manhal Ahmad Saleh Al-Hussein, Technical Engineering College of Mosul, Northern Technical University
  • Raid Rafi Omar Al-Nima Technical Engineering College of Mosul, Northern Technical University

Abstract

Palmprint biometrics is the best method of identifying an individual with a unique palmprint for every person.
The present paper formulates a new methodology towards
the identification of 3D palmprints using the Modified FourPatch Local Binary Pattern (MFPLBP). It improves upon the
conventional Four-Patch Local Binary Pattern (FPLBP) by integrating the adaptive weight with the improved texture extraction.
Both approaches are created to support the intricate surface
information of 3D palmprints. The MFPLBP can exactly capture
local variations and is noise and illumination invariant. There
are extensive experiments done in this paper and establish that
MFPLBP outperforms traditional LBP methods and other stateof-the-art methods in recognition rates. The experiments establish
that MFPLBP is a efficient and effective method of making use
of 3D palmprints in real-world biometric verification

Author Biography

Musab Tahseen Salahaldeen Al-Kaltakchi, College of Engineering, Mustansiriyah University, Baghdad

Dr. Musab T. S. Al-Kaltakchi is a lecturer in the Electrical Engineering Department, Mustansiriyah University, Baghdad-Iraq. He obtained his BSc in Electrical Engineering in 1996 and obtained his MSc in Communication and Electronics in 2004 from Mustansiriyah University. He was awarded a PhD degree in Electrical Engineering/ Digital Signal Processing from Newcastle University, UK in 2018. He is a member of the Institute of Electrical and Electronic Engineering (IEEE) and also in the Institute of Engineering and Technology (IET). His research interests include Speaker identification and verification, Speech and audio signal processing, Machine learning, Artificial intelligence, Pattern recognition, and Biometrics. He can be contacted at Email: musab.tahseen@gmail.com & at Email: m.t.s.al_kaltakchi@uomustansiriyah.edu.iq.

Additional Files

Published

2025-05-30

Issue

Vol. 71 No. 2 (2025)

Section

Image Processing

License

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