Home   >   CSC-OpenAccess Library   >    Manuscript Information
Full Text Available

(223.28KB)
This is an Open Access publication published under CSC-OpenAccess Policy.
Publications from CSC-OpenAccess Library are being accessed from over 74 countries worldwide.
Face Recognition using Improved FFT Based Radon by PSO and PCA Techniques
Hamid M. Hasan, Waleed A. AL.Jouhar, Majed A. Alwan
Pages - 26 - 37     |    Revised - 15-01-2012     |    Published - 21-02-2012
Volume - 6   Issue - 1    |    Publication Date - February 2012  Table of Contents
MORE INFORMATION
KEYWORDS
: Face recognition (FR), Radon Transform (RT), Fast Fourier Transform (FFT), Principal Component Analysis (PCA), Particle Swarm Optimization (PSO)
ABSTRACT
Abstract Face Recognition is one of the problems which can be handled very well using a Hybrid technique or mixed transform rather than single technique, it is a very well in terms of a good performance and a large size of the problem. In this paper we represent the using of the Fourier-Based Radon Transform which is improved by the Particle Swarm Optimization (PSO). PSO in this research is used to select the optimum directions (projection angles) that achieve a very high recognition rate and a fast computation. The number of directions selected using PSO is less than the number required by ordinary Radon. This leads to a small number of features. These number of features are reduced farther using PCA to produce a low number of features which used to represent faces in the database. Our method has been applied to ORL Database and achieves 100% recognition rate.
CITED BY (10)  
1 Ma, X., Liu, C., & Zhao, L. (2015). Face Fusion Recognition Based on Bit-Plane Image. Open Automation and Control Systems Journal, 7, 835-841.
2 Kourav, A. K., & Sharma, A. (2015). Multiresolution Transform Techniques in Digital Image Processing. International Journal of Computer Applications, 123(12).
3 Zhao, Z., & Li, B. (2015, October). Dynamically optimizing face recognition using PCA. In Control, Automation and Information Sciences (ICCAIS), 2015 International Conference on (pp. 123-127). IEEE.
4 Al-Yoonus, M. H., Al-Shargie, F., Al-Yoonus, M., & bin Zakaria, Z. (2014). Performance Analysis Comparative Study of Fingerprint Recognition Systems. International Review on Computers and Software (IRECOS), 9(7), 1154-1162.
5 Sable, A., & Chowdhary, G. (2014, November). Performance Comparison of Two Phase Face Recognition Algorithms based in Frequency Domain. In Proceedings of the 2014 International Conference on Information and Communication Technology for Competitive Strategies (p. 76). ACM.
6 Shah, S., Khan, S. A., & Riaz, N. (2013). Analytical Study of Face Recognition Techniques.
7 Li, Z., Yang, N., Xie, B., & Zhang, J. (2013). A two-phase face recognition method in frequency domain. Optik-International Journal for Light and Electron Optics, 124(23), 6333-6337.
8 Pheobe, O., DongJun, H., & Rimiru, R. (2013). Machine learning performance on face expression recognition using filtered backprojection in DCT-PCA domain. IJCSI International Journal of Computer Science Issues, 10(1), 145-153.
9 Kekre, H. B., Sarode, T. K., & Save, J. K. (2013). Classification of Image Database Using Independent Principal Component Analysis. International Journal of Advanced Computer Science and Applications (IJACSA), 4(7), 109-116.
10 Gogovi, G. K. (2013). Digital Image Processing Via Singular Value Decomposition (Doctoral dissertation, Department of Mathematics, Kwame Nkrumah University of Science and Technology).
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PdfSR 
1 Nilima B. Kachare, Vandana S. Inamdar, 2010, " Survey of Face Recognition Tecchniques", International Journal of Computer Applications(0975-8887), Volum 1-No.19,2010.
2 Patil A.M., Kolhe S.R. and Patil P.M., 2010,"2D Face Recognition Techniques:A Survay", International Journal of Machine Intelligence.
3 Thomas Heseltine, Nick Pears,Jim Austin,Zezhi Chen, 2003, "Face Recognition: A Comparison of appearance-Based approaches", Proc.VIIth Digital Image Computing :Techniques and Applications.,Sun C., Talbot H.,Ourselin S. and Adriaanen T. (10-12 Dec,2003,Sydny).
4 M. Chandra Mohan, V. Vijaya Kumar,K.V.Subbaiah,(2010)," A New Method of Face Recognition Based on Texture Feature Extraction on Individual Components of Face",International Journal of signal and Image Processing (Vol 1-2020/ISS.2)pp.69-74.
5 P.Abouzar, Yousefi,S.K.Setarehdan,(2007), "Hybrid WT Based-DCT Based Face Recogntion" , 2007 IEEE International Conference on Signal Processing and communications(ICSPC 2007). 24-27 November 2007, Dubai,United arab Emirates.
6 Zhan Shi, Minghui Du, Rongbing Huang,(2010),"A Trace Transform based on subspace method for Face Recognition", 2010 International Conference on Computer Application and System Modeling (ICCASM 2010).
7 Laika Karsili and Adnan Acan,2007,"A Radon Transform and PCA Hybrid for High Performance Face Recognition", IEEE International Symposium on Signal Processing and Information Technology.
8 Jamal A hmad Dargham et al. (2010) "Radon transform for face recognition", Artif Life Robotics(2010) 15:359-362,ISAROB 2010.
9 ZHANG Yuhua,WANG Xin,(2010),"Study of Finite Radon Transform in Face Recognition",2010 Second International Conference on Computer Modeling and Simulation.
10 Ergun Gumus, et al., "Eigenfaces and Support Vector Machine Approaches for Hybrid Face Recognition", The Online Journal on Electronics and Electrical Engineering (OJEEE) Vol(2)- No.4.
11 Zhang Lin,et al. "Infrared Face Recognition Based On Radon and Multiwavelet Transform" ,Proceedings of ICCTA 2009.
12 Yuehui Chen, Shuyan Jiang, Ajith Abraham, " Face Recognition Using DCT and Hybrid Flexible Neural Tree",2005IEEE,Development Program of Shandong under contract number SDSP2004-0720-03.
13 Jian Zhang,Xiany un Fei, " A New Method for Face Recognition Based on PCA Optimize Strategy"; 2010 International Conference on Computer Application and System Modeling (ICCASM)2010.
14 Dattatr V.Jadhao, Raghunath S.Holambe; "Feature Extraction and Dimensionality Reduction Using Radon and Fourier Transform with Application to Face Recognition", International Conference on Computational Intelligence and Multimedia Application 2007.
15 Rabab M. Ramadan and Rehab F. Abdel Kader; " Face Recognition Using Particle Swarm Optimization-Based Selected Features", International Journal of Signal Processing, Image Processing and Pattern Recognition Vol. 2, No. 2, June 2009.
16 Daming Shi. , Liying Zheng, and Jigang Liu," Advanced Hough Transform Using A Multilayer Fractional Fourier Method", IEEE Transactions on Image Processing, VOL, 19. NO, 6, JUNE 2010.
17 Patrick Etyngier et al., "Radon Space and Adaboost for Pose Estimation", Proceedings of the 18th International Conference on Pattern Recognition (ICPR'06) 2006 .
18 Mahmoud R.HEJAZI and YO Sung HO," Texture Analysis Using Modified Discrete Radon Transform", IEICE TRANS.INF. & SYST., VOL.E90-D, NO.2 FEBRUARY 2007.
19 S. Venturras, I. Flaounas ," Study of Radon Transformation and Application of its Inverse to NMR", Paper for " Algorithms in Molecular Biology" Course Assoc Prof. I. Emiris, 4 July, 2005.
20 Ming Jiang,Chih ting Wu," Wavelet Based Local Tomography" Mathematical Methods in Medical Imaging , Final Project, Math-6792 Spring 2003.
21 Jiangsheng You, Weiguo Lu, et al; " Image Maching for translation, rotation and uniform scaling by the Radon Transform",1998 IEEE.
22 Alec Banks, et al. " A review of particle swarm optimization. Part II: hybridization, combinatorial, multicriteria and constrained optimization, and indicative applications", Nat Comput (2008) 7:109-124, DOI 10.1007/s11047-007-9050-z.
23 Shih wei Lin and shih chieh Chen, " PSOLDA: A particle swarm optimization approach for enhancing classification accuracy rate of linear discriminant analysis", Applied Soft Computing 9 (2009) 1008-1015.
24 Millie Pant et al, "A New Quantum Behaved Particle Swarm Optimization",GECCO'08,July 12-16, 2008 Atlanta, Georgia. USA.
25 Leandro dos Santos Coelho," A quantum particle swarm optimizer with chaotic mutation operator", Chaos, Solutions and Fractals 37 (2008) 1409-1418.
26 O. Togla altinoz, et al. " Chaos Particle Swarm Optimization PID Controller for the Inverted Pendulum System", 2nd International Conference on Engineering Optimization, September 6- 9, 2010, Lsbon, Portugal.
27 Leandro dos Santos Coelho and Viviana Cocco Mariani, " A novel chaotic particle swarm ooptimization approach using Henon map and implicit filitering local search for load dispatch", Chaos, Solutions and Fractals 39(2009) 510-518.
28 Qing Zhang, et al. " Fast Multi swarm Optimization with Cauchy Mutation and Crossover operation", Puplications of China University of Geosciences, School of Computer, Wuhan, P.R.China, 430074.
29 Yanjun Yan and Lisa ann Osadciw, "Varying Dimensional Particle Swarm Optimization", 2008 IEEE swarm Intelligence symposim , St. Louis Mo USA, September 21-23,2008.
30 R. V. Kulkarni and G.K. Venayagamoorthy, " A
31 Yanj Yan, Ganapathi Kamath and Lisa ann Osadciw, " Feature Selection Optimization by Discrete Particle swarm Optimization for Face recognition", Syracuse University , Syracuse , NY, USA 13244.
32 Hong Pan, LiangZhengXia, and Truong Q.Nguyen," Robust Object detection Scheme using feature selection", Proceeding of 2010 IEEE 17th International Conference on Image Processing , September 26-29, 2010, Hong Kong.
33 Osslan Osiris Aergara Villegas and Viancy Guadalupe," a Novel Evolutionary Face algorithm Using Particle Swarm Optimization ", 2009 Fith International Conference on Signal Image Technology and Internet Based Syetems.
34 Lanzarini Laura , et al. " Face Recognition Using SIFT and Binary PSO Descriptors", 2010 Proceedings of the ITI 2010 32th Int. Conf. on Information technology Interfaces, June 21- 24,2010, Cavtat, Croatia.
35 Rajinda Senaratne, et al. " Face Recognition by Extending Elastic Bunch Graph Matching with Particle Swarm Optimization", Journal of Multimedia , VOL. 4, No. 4, August 2009.
36 Ming Li, et al. " Application of Improved CPSO-SVM Approach in Face Recognition", 2009 Internaltional Conference on Artificial Intelligence and Com[utational Intelligence.
37 Xiaorong Pu, Zhang YI, Zhongjie Fang," Holistic and partial facial features fution by binary particle swarm optimization", Neural Comput & Applic (2008) 17:481-488.
38 Belhumeur PN, Hespanala JP, Kriegman DJ (1997) Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Trans Pattern Anal Mach Intell 19(7):711-720.
Mr. Hamid M. Hasan
University of technology - Iraq
hamid2012net@gmail.com
Professor Waleed A. AL.Jouhar
Electrical Eng. Dept. - Iraq
Dr. Majed A. Alwan
Electrical Eng. Dept , - Iraq