Face Recognition for Access Control using PCA Algorithm
|International Journal of VLSI & Signal Processing|
|© 2017 by SSRG - IJVSP Journal|
|Volume 4 Issue 2|
|Year of Publication : 2017|
|Authors : Opeyemi Oyelesi and Akingbade Kayode Francis|
How to Cite?
Opeyemi Oyelesi and Akingbade Kayode Francis, "Face Recognition for Access Control using PCA Algorithm," SSRG International Journal of VLSI & Signal Processing, vol. 4, no. 2, pp. 22-27, 2017. Crossref, https://doi.org/10.14445/23942584/IJVSP-V4I3P105
In this paper, an efficient and easy to implement method for face recognition using Principal Component analysis (PCA) which employs eigenface approach is presented. In recent years, when research into the field of face recognition started, principle component analysis (PCA) was the first major breakthrough that proved successful and it has remained one of the most popular methods representation methods for face images. It not only reduces the dimensionality of the image it also retains some of the variation in the image data. The reduction in dimensionality ensures that it can be applied to real time applications since it requires lesser time for processing.
Biometrics, Face Recognition, Face detection, Principal Component Analysis, Jones-Viola Face Detection Algorithm.
 Kar, S., Hiremath, S., Joshi, D.G., Chadda, V.K, and Bajpai, A. A MultiAlgorithmic Face Recognition System. International Conference on Advanced Computing and Communication. December 20-23, 2006 ADCOM 2006. 321 - 326.
 Jain, A. K., Ross, A., and Prabhakar, S. An Introduction to Biometric Recognition. IEEE Transaction on Circuits and System for Video Technology. (2004) 14(1): 4-20.
 Çarıkçı, M., and Özen, F., A Face Recognition System Based on Eigenfaces Method, Procedia Technology. 118-123; 2012
 Chaoyang, Z., Zhaoxian, Z., Hua, S., and Fan, D. Comparison of Three Face Recognition Algorithms. International Conference on Systems and Informatics. May 19-20, 2012. ICSAI. 2012. 1896-1900.
 Kirby, M., and Sirovich, L. Application of The Karhunen- Loeve Procedure for The Characterization of Human Faces. IEEE Transaction on Pattern Analysis and Machine Intelligence. 1990. 12(1): 103-108.
 Lih-Heng, C., Aslleh, S.H., and Chee-Ming, T., PCA,LDA and Neural Network for Face Identification IEEE Conference on Industrial Electronics and Applications. May 25-27, 2009. ICIEA 2009. 1256-1259
 Riddhi, C., and Neha, P., Details Study On 2D Face Recognition Technique Using Local And Global Features. Indian Streams Research Journal. 2013. 3(2):1-17.
 Kim K (2003) Face Recognition using principal component analysis. Department of Computer Science University of Maryland, College Park