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Comparative Assessment of Performance of LDA, LR and SVM in the Application of Face Detection

S. Paul1 , P. Rakshit2 , J. Mistri3 , I. Nath4 , S. Biswas5 , D. Singh6 , R. Sen7

Section:Research Paper, Product Type: Journal Paper
Volume-08 , Issue-01 , Page no. 44-48, Feb-2020

Online published on Feb 28, 2020

Copyright © S. Paul, P. Rakshit, J. Mistri, I. Nath, S. Biswas, D. Singh, R. Sen . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S. Paul, P. Rakshit, J. Mistri, I. Nath, S. Biswas, D. Singh, R. Sen, “Comparative Assessment of Performance of LDA, LR and SVM in the Application of Face Detection,” International Journal of Computer Sciences and Engineering, Vol.08, Issue.01, pp.44-48, 2020.

MLA Style Citation: S. Paul, P. Rakshit, J. Mistri, I. Nath, S. Biswas, D. Singh, R. Sen "Comparative Assessment of Performance of LDA, LR and SVM in the Application of Face Detection." International Journal of Computer Sciences and Engineering 08.01 (2020): 44-48.

APA Style Citation: S. Paul, P. Rakshit, J. Mistri, I. Nath, S. Biswas, D. Singh, R. Sen, (2020). Comparative Assessment of Performance of LDA, LR and SVM in the Application of Face Detection. International Journal of Computer Sciences and Engineering, 08(01), 44-48.

BibTex Style Citation:
@article{Paul_2020,
author = {S. Paul, P. Rakshit, J. Mistri, I. Nath, S. Biswas, D. Singh, R. Sen},
title = {Comparative Assessment of Performance of LDA, LR and SVM in the Application of Face Detection},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2020},
volume = {08},
Issue = {01},
month = {2},
year = {2020},
issn = {2347-2693},
pages = {44-48},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1398},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1398
TI - Comparative Assessment of Performance of LDA, LR and SVM in the Application of Face Detection
T2 - International Journal of Computer Sciences and Engineering
AU - S. Paul, P. Rakshit, J. Mistri, I. Nath, S. Biswas, D. Singh, R. Sen
PY - 2020
DA - 2020/02/28
PB - IJCSE, Indore, INDIA
SP - 44-48
IS - 01
VL - 08
SN - 2347-2693
ER -

           

Abstract

In biometrics research face detection and recognition is a very popular topic and it has distinct advantages because of its non-contact process. This type of technology extensively draws attention due to its huge application and market value. like video surveillance system for detecting suspicious object. Face based recognition system is more popular over other biometrics because of its uniqueness. Face recognition is very difficult task because human face is a dynamic object and has variability in its appearance. So, here accuracy and speed of recognition is Min issue. The purpose of the paper is correctly recognized a person from an image face or a video. To correctly identify a person we have used three techniques: Linear discriminant analysis (LDA), Logistic Regression (LR) and support vector Machine (SVM) techniques with Principle Components Analysis (PCA) which extract the features and reduce dimensionality. The LDA and LR technique produce more accurate result compare to other methods. This paper achieved 93% successful recognition rate for recognizing different face database.

Key-Words / Index Term

Face detection, Face Recognition, PCA, SVM, LDA, and LR

References

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