E-Voting For Universities Using Face Recognition

Addepalli Lakshmi Venkata Sai Kumar, Mandapaka Kundana, Palisetty Sandhya, Edupalli Tarun Rohit, K. Udayasri

Abstract


This report describes an online voting system designed to meet the needs of colleges and universities. Voting is a widely spread, democratic way of making decisions and can be used for electing student presidents and class representatives at the college level. The main objective of the proposed system is to develop a more secure and user-friendly voting system compared to the existing methods. The process of voting is critical in terms of safety and security. The proposed system allows the voters to scan their faces, which is then matched with the already saved images within the database. There is a high chance that the voter's choice to be revealed in the traditional system, which is not the case in this proposed system. By using face recognition, it provides enough security to eradicate the dummy votes. The system also provides clear visualization of data regarding the percentage of total votes cast, the percentage of votes each party secured, and the final winner in the election.


References


Pandit, Varad, Prathamesh Majga onkar, Pratik Meher, Shashank Sapaliga, and Sachin Bojewar, “Intelligent security lock.” In Trends in Electronics and Informatics (ICEI), 2017 International Conference on pp. 713-716. IEEE, 2017.

Bhimanwar, Chinmay, Rupesh Biradar, Nikhil Bhole, and Milind Rane. "Face Identification." International Journal of Engineering Science11923 (2017).

Ishani Mondal, Sombuddha Chatterjee. “Secure and Hassle-Free EVM Through Deep Learning Based Face Recognition.” International Conference on Machine Learning, Big Data, Cloud Computing and Parallel Computing (COMITCon). IEEE, 2019

S. Kumar and E. Walia, “Analysis of electronic voting system in various countries,” International Journal on Computer Science and Engineering, vol. 3, no. 5, pp. 1825-1830, 2011.

D. Nikram, D. Shetiye, and D. Bhorite, “A critical study of electronic voting machine EVM utilization in electronic procedure,” International Journal of Trend in Scientific Research and Development, vol. Special Issue, pp. 1-3, 03 2019.

S. Ravi and D.P. Mankame, “Multimodal biometric approach using fingerprint, face and enhanced iris features recognition,” in 2013 International Conference on Circuits, Power and Computing Technologies (ICCPCT), IEEE, 2013, pp. 1143-1150.

D. Menotti, G. Chiachia, A. Pinto, W. R. Schwartz, H. Pedrini, A. X.Falcao, and A. Rocha, “Deep representations for iris, face, and fingerprint spoofing detection,” IEEE Transactions on Information Forensics and Security, vol. 10, no. 4,pp. 864–879, 2015.

J. Soldera, G. Schu, L. R. Schardosim, and E. T. Beltrao, “Facial biometrics and applications,” IEEE Instrumentation & Measurement Magazine, vol. 20, no. 2,pp. 4–30, 2017.

S. Kumar, S. Nandury, and S. Raj, “An extended client server architecture inmobile environment,” International Journal of Computer Engineering and Applications, vol. 5, pp. 97–107, 02 2014.

T. Ko, “Multimodal biometric identification for large user population using fingerprint, face and iris recognition,” in 34th Applied Imagery and Pattern Recognition Workshop (AIPR’05), 2005, pp. 6 pp.–223.


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