Journal of Electrical and Electronic Engineering
Volume 3, Issue 2-1, March 2015, Pages: 62-65
Received: Dec. 23, 2014;
Accepted: Dec. 27, 2014;
Published: Jan. 27, 2015
Views 3482 Downloads 200
Mozhde Elahi, Department of Control Engineering, Gonabad University, Gonabad, Iran
Mahsa Gharaee, Department of Electronic Engineering, Gonabad University, Gonabad, Iran
In this paper Performance of Principle Component Analysis and Discrete Cosine Transform methods for feature reduction in face recognition system is compared. In face recognition system, feature extraction is based on wavelet transform and Support Vector Machine classifier for training and recognition is employed. According to experimental results on ORL face dataset the PCA method gives better performance compared to using DCT method.
Performance Comparison for Face Recognition using PCA and DCT, Journal of Electrical and Electronic Engineering. Special Issue: Research and Practices in Electrical and Electronic Engineering in Developing Countries.
Vol. 3, No. 2-1,
2015, pp. 62-65.
M.Sharkas, ‘Application of DCT Blocks with Principal Component Analysis for Face Recognition’ Proceedings of the 5th WSEAS Int. Conf. on SIGNAL, SPEECH and IMAGE PROCESSING, Corfu, Greece, August 17-19, 2005 (pp107-111)
X.M. Wand, CH. Huang, G.Y. Ni, J.G. Liu, ‘Face Recognition Based on Face Gabor Image and SVM’ 978-1-4244-4131-0/09/$25.00 ©2009 IEEE
M. Wang, H. Jiang, and Y. Li, ‘ Face Recognition Based on DWT/DCT and SVM’ 2010 International Conference on Computer Application and System Modeling (ICCASM 20ID)
B. Luo, Y. Zhang, and Y.H. Pan, ‘ Face Recognition Based on Wavelet Transform and SVM’ Proceedings of the 2005 IEEE, International Conference on Information Acquisition ,June 27 - July 3, 2005, Hong Kong and Macau, China
M. S. Sarfraz, O. Hellwich and Z. Riaz, ‘ feature Extraction and Representation for Face Recognition’ ISBN 978-953-307-060-5, Published: April 1, 2010 under CC BY-NC-SA 3.0 license
M. Mazloom, S. Kasaei, and H. Alemi, ‘Construction and Application of SVM Model and Wavelet-PCA for Face recognition’ 2009 Second International Conference on Computer and Electrical Engineering
I.K. Timotius, I. Setyawan, and A.A. Febrianto, ‘Face Recognition between Two Person using Kernel Principal Component Analysis and Support Vector Machines’International Journal on Electrical Engineering and Informatics - Volume 2, Number 1, 2010
G. Yu, S.V. Kamarthi, ‘A cluster-based wavelet feature extraction method and its application’ , Engineering Applications of Artificial Intelligence 23 (2010) 196–202, Accepted 27 November 2009
R.C. Palero, R.G. Girones and F. Ballester-Merelo, ‘Flexible architecture for the implementation of the two-dimensional discrete wavelet transform (20-0WT) oriented to FPGA devices’, Microprocessors and Microsystems, vol. 28, pp. 509-518,2004
S. G. Mallalt, ‘Multifrequencychannal decompositions of images and wavelet models’, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 37, pp. 209 1-2 1 10, 1989.
L. Xian, Y. Sheng, W. Qi, and L. Ming, ‘Face Recognition Based on Wavelet Transform and PCA’ 2009 Pacific-Asia Conference on Knowledge Engineering and Software Engineering
H. Wang, S. Yang, and W. Liao, ‘An Improved PCA Face Recognition Algorithm Based on the Discrete Wavelet Transform and the Support Vector Machines’ 2007 International Conference on Computational Intelligence and Security Workshops
M. Mazloom, S. Kasaei, ‘Combination of Wavelet and PCA for Face Recognition’ GCC Conference (GCC), 2006 IEEE , E-ISBN 978-0-7803-9591-6, E-ISBN 978-0-7803-9591-6, INSPEC Accession Number 11747056
V.p.Vishwakarma, S. Pandey, and M.N. Gupta, ‘A Novel Approach for Face Recognition Using DCT Coefficients Re-scaling for Illumination Normalization’ 15th International Conference on Advanced Computing and Communications, 0-7695-3059-1/07 $25.00 © 2007 IEEE, DOI 10.1109/ADCOM.2007.12
K. Manikantan, V. Govindarajan, ‘Face Recognition using Block Based DCT Feature Extraction’, Journal of Advanced Computer Science and Technology, 1 (4) (2012) 266-283
A.R. Chadha, P.P. Vaidya, and M.M. Roja, ‘Face Recognition Using Discrete Cosine Transform for Global and Local Features’, Proceedings of the 2011 International Conference on Recent Advancements in Electrical, Electronics and Control Engineering (IConRAEeCE) IEEE Xplore: CFP1153R-ART; ISBN: 978-1-4577-2149-6