Volume 2, Issue 4, December 2017, Page: 152-168
Radial Basis Function Neuroscaling Algorithms for Efficient Facial Image Recognition
Vincent A. Akpan, Department of Biomedical Technology, The Federal University of Technology, Akure, Nigeria
Joshua B. Agbogun, Department of Computer Science, Kogi State University, Anyigba, Nigeria
Michael T. Babalola, Department of Physics Electronics, Afe Babalola University, Ado-Ekiti, Nigeria
Bamidele A. Oluwade, Department of Computer Science, University of Ilorin, Ilorin, Nigeria
Received: Sep. 30, 2017;       Accepted: Nov. 9, 2017;       Published: Dec. 28, 2017
DOI: 10.11648/j.mlr.20170204.16      View  1144      Downloads  72
Abstract
A Radial basis function neural network-based probabilistic principal component analysis (RBFNN-PPCA) on image recognition based on facial recognition was made. The variational properties of face images are investigated with Eigenfaces algorithm to validate the proposed RBFNN-PPCA algorithm and technique for enhanced optimal image recognition system design. Ten different face image samples for each one hundred different individuals with their corresponding bio-data were taken under different light intensities were cropped and pre-processed. The resulting one thousand face image samples were split into 80% as the training set which constitutes the database of known face images and 20% as the test set which constitutes unknown faces images. Analysis was made on the one thousand face images based on the proposed RBFNN-PPCA algorithm and the Eigenfaces algorithm. The two algorithms were applied simultaneously for enhanced optimal face recognition, and the simulation results show that the proposed face image evaluation techniques as well as the proposed RBF neuroscaling algorithm recognizes a known face image or rejects an unknown face based on the database contents to a high degree of accuracy. The proposed face recognition strategy can be adapted for the design of on-line real-time embedded face recognition systems for public, private, business, commercial or industrial applications.
Keywords
Eigenfacess, Face Recognition, Neural Network (NN), Neuroscaling, Probabilistic Principal Component Analysis (PPCA), Radial Basis Function (RBF), Singular Value Decomposition (SVD)
To cite this article
Vincent A. Akpan, Joshua B. Agbogun, Michael T. Babalola, Bamidele A. Oluwade, Radial Basis Function Neuroscaling Algorithms for Efficient Facial Image Recognition, Machine Learning Research. Vol. 2, No. 4, 2017, pp. 152-168. doi: 10.11648/j.mlr.20170204.16
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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