Abstract
In this paper a new authentication technique in online voting system using facial recognition of the voter is used. In India, currently there are two types of voting system in practice.
They are secret Ballet paper and Electronic Voting Machines (EVM), but both of the process have some limitation or demerits. In India online voting has not been yet implemented because of security purpose.
The current voting system is not safe and secure too. The voters need to go to distributed places like polling booths and stand in a long queue to cast their vote in particular constitution, because of these reasons most of the people misses their chance of voting.one area to one.
The voter who is not eligible can also cast its vote by fake means which may leads to many problems. That’s why in this project we have to propose a system or way for voting which is very effective or useful in voting. In our approach we have three level of security in voting process. This smart voting project is help-full for beginners to analyze the e-voting system.
Introduction to smart voting system through face recognition
Now a day in India two types of method are used for voting. The first method is secret ballot paper, in which lots of paper are used and second method is EVM (electronic voting machine) which is used since 2003.
we have to propose a method or way for online voting that is more secure than the existing system. In this proposed project face detection and recognition concept is used to identify the exact person. In this project three step, The first one is Unique id number verification, and of verification is election commission id or voter card number.
Second step sent mail to unique id and otp, after main face recognition using open cv algorithm once done next, final step to vote cast in particular constitution. This project is used to voter to elect the right person.
System Architecture Online Voting System using facial recognition
H/w and S/W requirements of smart voting project
Hardware:
Computer : System.
Ram : 1GB
Rom : 32GB
Software:
Technology : Machine Learning.
Front End : GUI-tkinter.
IDLE : python 3.10.4
Virtual Envs : Anaconda
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