An Enhanced LBPH Algorithm for Robust Face Feature Extraction

Solomon Anab; Godbless Mensah; Edward Yellakuor Baagyere; Mustapha Adamu Mohammed

doi:10.36948/ijfmr.2024.v06i05.27853

An Enhanced LBPH Algorithm for Robust Face Feature Extraction

Author(s)	Solomon Anab, Godbless Mensah, Edward Yellakuor Baagyere, Mustapha Adamu Mohammed
Country	Ghana
Abstract	From security systems to human-computer interaction, face recognition technology is a key component in many different applications. In this domain, the local binary pattern histogram (lbph) algorithm has shown great promise due to its ability in texture-based feature extraction and robustness. In this study, the performance of lbph algorithm is improved by optimising important parameters: radius, number of neighbours and grid configuration. Tweaking these parameters systematically enable us to get the most success out of this algorithm. Lbph algorithm parameters has been tuned into a 5x7 dimensional matrix, which gives us total of 35 grids with equal width and height pixels. In other words, one central pixel plus 34 neighbouring pixels where the radii of 3 square neighbourhoods can be adjusted. The study combines the experimental exploration with fine-tuning via machine learning approaches to optimize lbph algorithm. Finally, we have provided experimental results on intra-class and inter-class feature distribution analysis conducted on selected images taken under constraints and unconstraint environments. The performance of our novel 34N-LBPH algorithm showed very low values by obtaining intra-class average means of 0.031, 0.078, and 0.101 for three classes under constraint environment indicating the proposed 34n-lbph is robust for facial feature extraction. The findings suggest that our enhanced algorithm, 34 neighbour linear binary pattern Histogram (34N-LBPH) can effectively handle variations in lighting, expressions and occlusions, contributing to the advancement of facial feature extraction for face recognition.
Keywords	Face recognition, LBPH, Algorithm, Parameters, Intra and Inter-Class, Analysis.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 6, Issue 5, September-October 2024
Published On	2024-10-06
Cite This	An Enhanced LBPH Algorithm for Robust Face Feature Extraction - Solomon Anab, Godbless Mensah, Edward Yellakuor Baagyere, Mustapha Adamu Mohammed - IJFMR Volume 6, Issue 5, September-October 2024. DOI 10.36948/ijfmr.2024.v06i05.27853
DOI	https://doi.org/10.36948/ijfmr.2024.v06i05.27853
Short DOI	https://doi.org/g795g3

View / Download PDF File

E-ISSN 2582-2160

doi

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads

Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 6 Isu 6 Cover Page Vol 6 Isu 5 Cover Page Vol 6 Isu 4

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9898-5948-55	editor@ijfmr.com

International Journal For Multidisciplinary Research

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

An Enhanced LBPH Algorithm for Robust Face Feature Extraction

Share this