PCA-based dimensionality reduction for face recognition

Md. Abu Marjan (Hajee Mohammad Danesh Science and Technology University)
Md. Rashedul Islam (Hajee Mohammad Danesh Science and Technology University)
Md. Palash Uddin (Hajee Mohammad Danesh Science and Technology University)
Masud Ibn Afjal (Hajee Mohammad Danesh Science and Technology University)
Md. Al Mamun (Rajshahi University of Engineering & Technology)

TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 19, No 5: October 2021

In this paper, we conduct a comprehensive study on dimensionality reduction (DR) techniques and discuss the mostly used statistical DR technique called principal component analysis (PCA) in detail with a view to addressing the classical face recognition problem. Therefore, we, more devotedly, propose a solution to either a typical face or individual face recognition based on the principal components, which are constructed using PCA on the face images. We simulate the proposed solution with several training and test sets of manually captured face images and also with the popular Olivetti Research Laboratory (ORL) and Yale face databases. The performance measure of the proposed face recognizer signifies its superiority.