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  A Study Analysis on Face Recognition and Various Methodologies  
  Authors : Michael Farayola; Aman Dureja; Ajay Dureja
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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

Figures :01

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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.


[1] A. Bansal, "A study of Factors Affecting Face Recognition", International Journal of Advanced in Management, Technology and Engineering Sciences, Volume 8, Issue II, FEB/2018, ISSN NO: 2249-7455. [2] V. H. Mankar, "A Review Paper on Face Recognition Techniques" ISSN: 2278-1323, OCT/2012. [3] G. S. Mandal's, IEEE Student Member, "Evaluation of Feature Extraction Techniques using Neural Network as a Classifier: A Comparative Review for face Recognition" 2018 IJSRST | Volume 4 | Issue 2 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X. [4] Rajesh A, "Gender Recognition from Face Image Based on Textural Analysis and Machine Learning Approach", 2018 IJSRSET | Volume 4 | Issue 1 | Print ISSN: 2395-1990 | Online ISSN: 2394-4099. [5] S. Arya, A. Agrawal, "Face Recognition with Partial Face Recognition and Convolutional Neural Network", International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 7, Issue 1, January 2018, ISSN: 2278 - 1323. [6] Q. Hua, Y. Liu, L. Sun, J. F. Miazonzama, "Face Recognition using Locality Preserving Projection on Wavelet Subband and Artificial Neural Network", International Journal of Computer Trends and Technology (IJCTT) - Volume 55 Number 1 January 2018. [7] S. Shukla, A. Helonde, S. Raut, S. Salode, J. Zade, "Random Keypad and Face Recognition Authentication Mechanism", IRJET, e-ISSN: 2395- 0056, Volume: 05 Issue: 03 | Mar-2018, p-ISSN: 2395-0072. [8] S. K. Bhattacharyya, K. Rahul, "Face Recognition by Linear Discriminant Analysis", International Journal of Communication Network Security, ISSN: 2231 - 1882, Volume-2, Issue-2, 2013. [8] O. Faruqe, A. M. Hasan, "Face Recognition Using PCA and SVM", Sep/2009 DOI:10.1109/ICASID.2009.5276938, Source: IEEE Xplore. [9] J. Shermina, "Application of Locality Preserving Projections in Face Recognition", (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 1, No. 3, Sep/ 2010. [10] S. A. Khan, "Factors affecting the recognition accuracy of facial expressions", Volume 1 Issue 4 - 2017. [11] J. Mazanec, M. Meli?sek, M. Oravec, J. Pavlovi?cov´a "Support Vector Machines, Pca And Lda In Face Recognition", Journal of ELECTRICAL ENGINEERING, VOL. 59, NO. 4, 2008, 203-209. [12] D. N. Parmar, B. B. Mehta, "Face Recognition Methods & Applications", Divyarajsinh N Parmar et al, Inc. Computer Technology & Applications 4 (1),84-86, ISSN:2229-6093, March 2014.