A Study Analysis on Face Recognition and Various Methodologies

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Authors
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References

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

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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 face recognition.

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 learning.

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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