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Smart Voting System through Facial Recognition
Nilam Choudhary1 , Shikhar Agarwal2 , Geerija Lavania3
Section:Research Paper, Product Type: Isroset-Journal
Vol.7 ,
Issue.2 , pp.7-10, Apr-2019
CrossRef-DOI: https://doi.org/10.26438/ijsrcse/v7i2.710
Online published on Apr 30, 2019
Copyright © Nilam Choudhary, Shikhar Agarwal, Geerija Lavania . 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: Nilam Choudhary, Shikhar Agarwal, Geerija Lavania, “Smart Voting System through Facial Recognition,” International Journal of Scientific Research in Computer Science and Engineering, Vol.7, Issue.2, pp.7-10, 2019.
MLA Style Citation: Nilam Choudhary, Shikhar Agarwal, Geerija Lavania "Smart Voting System through Facial Recognition." International Journal of Scientific Research in Computer Science and Engineering 7.2 (2019): 7-10.
APA Style Citation: Nilam Choudhary, Shikhar Agarwal, Geerija Lavania, (2019). Smart Voting System through Facial Recognition. International Journal of Scientific Research in Computer Science and Engineering, 7(2), 7-10.
BibTex Style Citation:
@article{Choudhary_2019,
author = {Nilam Choudhary, Shikhar Agarwal, Geerija Lavania},
title = {Smart Voting System through Facial Recognition},
journal = {International Journal of Scientific Research in Computer Science and Engineering},
issue_date = {4 2019},
volume = {7},
Issue = {2},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {7-10},
url = {https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=1266},
doi = {https://doi.org/10.26438/ijcse/v7i2.710}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i2.710}
UR - https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=1266
TI - Smart Voting System through Facial Recognition
T2 - International Journal of Scientific Research in Computer Science and Engineering
AU - Nilam Choudhary, Shikhar Agarwal, Geerija Lavania
PY - 2019
DA - 2019/04/30
PB - IJCSE, Indore, INDIA
SP - 7-10
IS - 2
VL - 7
SN - 2347-2693
ER -
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Abstract :
Facial recognition is a category of biometric software which works by matching the facial features. We will be studying the implementation of various algorithms in the field of secure voting methodology. There are three levels of verification which were used for the voters in our proposed system. The first is UID verification, second is for the voter card number, and the third level of verification includes the use of various algorithms for facial recognition. In this paper, we will provide a comparative study between these algorithms, namely: Eigenface, FisherFace & SURF.
Key-Words / Index Term :
Smart Voting; Facial Recognition; EigenFace ; FisherFace; SURF
References :
[1] A. Baumberg, “Reliable feature matching across widely separated views”, in CVPR, 2000
[2] F. Song, D. Zhang, J. Wang, H. Liu, and Q. Tao, "A parameterized direct LDA and its application to face recognition," Neurocomputing, Vol.71, 2007.
[3] H. Bay, T. Tuytelaars, L. Van Gool, “SURF: speeded up robust features”, in ECCV, 2006.
[4] KashifHussainMemon, Dileep Kumar and Syed Muhammad Usman, “Next Generation A Secure EVoting System Based On Biometric Fingerprint Method”, 2011.
[5] P. Belhumeur, J. Hespanha, and D. Kriegman, “Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(7):711--720, 1997.
[6] P. Viola and M. J. Jones, "Robust real-time face detection," International Journal of Computer Vision, Vol. 57, pp. 137-154, 2004.
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