Home
Author Guide
Editor Guide
Reviewer Guide
Published Issues
Special Issue
Introduction
Special Issues List
Sections and Topics
Sections
Topics
journal menu
Aims and Scope
Editorial Board
Indexing Service
Article Processing Charge
Open Access
Copyright and Licensing
Preservation and Repository Policy
Publication Ethics
Editorial Process
Contact Us
General Information
ISSN:
1798-2340 (Online)
Frequency:
Monthly
DOI:
10.12720/jait
Indexing:
ESCI (Web of Science)
,
Scopus
,
CNKI
,
etc
.
Acceptance Rate:
19%
APC:
500 USD
Average Days to Accept:
135 days
Journal Metrics:
Impact Factor 2022: 1.0
3.1
2022
CiteScore
49th percentile
Powered by
Editor-in-Chief
Prof. Kin C. Yow
University of Regina, Saskatchewan, Canada
I'm delighted to serve as the Editor-in-Chief of
Journal of Advances in Information Technology
.
JAIT
is intended to reflect new directions of research and report latest advances in information technology. I will do my best to increase the prestige of the journal.
What's New
2024-03-28
Vol. 15, No. 3 has been published online!
2024-02-26
The papers published in Vol. 15, Nos. 1&2 have been registered with Crossref.
2024-02-26
Vol. 15, No. 2 has been published online!
Home
>
Published Issues
>
2020
>
Volume 11, No. 3, August 2020
>
Global Facial Recognition Using Gabor Wavelet, Support Vector Machines and 3D Face Models
José Augusto Cadena Moreano and Nora Bertha La Serna Palomino
National University of San Marcos, Lima, Peru
Abstract
—The present research is aimed to develop an optimal method for face recognition based on wavelet Gabor filtering, feature extraction, and Support Vector Machine (SVM) using the BU-3DFE database containing 3D face models. Process for working with 350 models corresponding to 50 persons, i.e. 10 models per person divided seven for training and three for testing. The proposed technique involves projecting the face models obtained from the BU-3DFE database to the three planes using Matlab 2015a functions, and then, treating them as 2D images for recognition. The aim of this work is to achieve efficient 3D facial recognition with acceptable performance. As a result, the highest obtained value was 97.3% for SVM (kernel cubical). The results obtained for the proposed approach were compared with those of other recent 3D facial recognition methods to evaluate the potential of the former. Contribution of the present research is to facilitate urban security through providing a more efficient way for recognition of people who threaten the peace and tranquility of society, public or private institution, etc.
Index Terms
—databases, support vector machine, facial recognition, Gabor, feature extraction
Cite: José Augusto Cadena Moreano and Nora Bertha La Serna Palomino, "Global Facial Recognition Using Gabor Wavelet, Support Vector Machines and 3D Face Models," Journal of Advances in Information Technology, Vol. 11, No. 3, pp. 143-148, August 2020. doi: 10.12720/jait.11.3.143-148
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License (
CC BY-NC-ND 4.0
), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.
5-IJMLC-262-Final_Peru
PREVIOUS PAPER
Deep Learning Based Security Management of Information Systems: A Comparative Study
NEXT PAPER
Transcription of Guitar Chords from Acoustic Audio