• Deepak Kumar
• Latha Banda

face Recognition is one of the key areas that is considered to be always growing as there is no completely secure and accurate approach that can recognize the correct match. Over the years many techniques for face recognition has been evolved and most of it are quite accurate under specified conditions that is pose, illumination and expressions. This paper is a take on the Principal component analysis technique that use dimensionality reduction and eigenface for face recognition. Gray scale equalization is used earlier to achieve better results. We used three separate databases to obtain the result. ORL, Yale, CMU and other popular databases are used by researchers in experimenting and implementing the methods proposed by them.

Face Detection, Face Recognition, PCA, Kernel-PCA, 2DPCA, EWPCA, SVD, Eigenface

"Face Recognition System: An Approach Based on Principal Component Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.23-26, June-2019, Available :http://www.jetir.org/papers/JETIR1906F09.pdf

"Face Recognition System: An Approach Based on Principal Component Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp23-26, June-2019, Available at : http://www.jetir.org/papers/JETIR1906F09.pdf