Face Recognition is a crucial concept in today's world which has helped enormously in the areas of security, biometric,
surveillance, access control and many more. It deals with the identification of human faces, which serves as an individual's identity.
Every individual can be distinguished and recognized by their faces. Numerous methods have been used extensively over the decades to
enhance and boost the technology of face recognition system accurately. These are PCA, LDA, LPP, ICA, SVM and many hybrid
combinations of these techniques. In this paper, we will study an overview of face recognition, some methods used over time and
common factors that affect the poor acceptability of face recognition system.
Published In:IJCSN Journal Volume 9, Issue 2
Date of Publication : April 2020
Pages : 46-50
Tables : --
Michael Farayola :
is pursuing his Master of Technology degree
in Computer Science and Engineering from PDM University,
India. He received his Bachelor of Technology degree in Pure and
Applied Mathematics in 2015 from FUTMINNA, Nigeria. His
research interests include data science, machine learning and
Aman Dureja :
is pursuing his PhD from GGSIPU, New Delhi. He
received his Master of Technology degree from MDU University
in year 2010 and Bachelor of Technology from Bhiwani Institute
of Technology and Sciences in year 2007. Currently working as
Assistant Professor in Department of Computer Science and
Engineering, PDM University since 2010. He has published more
than 20 research papers in reputed International Journals
including Scopus Indexed and conferences including IEEE. His
main research work focus on machine learning and deep
Ajay Dureja :
Department of Computer Science and Engineering, PDM University,
124507, Haryana, India
Face Recognition, Feature Extraction, Accuracy
Face recognition is a part of machine learning and
pattern recognition capable of identifying a face either
from a digital image or video stream. It is a fast-growing
technology development in the areas of security,
biometric, authentication applications and access control
due to its uniqueness. It holds lot of potential because it
is a highly effective biometric technology. This paper has
works towards an overview of face recognition, its
methodologies and common adverse effect on face
recognition. In summary, LDA always achieve optimum
face recognition rate, although it can be quite unstable
due to high sensitivity to methodological settings.
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