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.


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