Smart Voting System Through Face Recognition

Elections are essential defining characteristics of any democracy in which citizens express their choice or articulate their opinions during voting. Voting systems have progressed from simple handwritten ballots to internet voting system in bounds and leaps. This venture intends to create elegant voting system based on facial identification technology that allows every voter in INDIA to vote from anywhere in India at the near polling booth in their location. This venture is used to keep biometric security at a high level. The voter information is saved in the server database. Before beginning the voting procedure, the voter must position in facade of the computer, where the camera will examine the voter’s picture. The microcontroller reads the information and delivers it to the web application through the serial port. The individual record is maintained by the web application software. If a person’s age is less than 18 years old, and he tries to vote again using his face sample, the web page will indicate that he is not entitled to vote. After the voting process is over, the election commission may log in and examine the results of the election. It can also reset the votes and update the candidate results.

I. Introduction

In India, we now have two types of voting mechanisms: the secret Ballet paper and the Electronic Voting Machines (EVM). However, the voting process has various flaws and shortcomings, which is why the existing system is not very safe and secure. We propose three stages of verification in our selected system research, which is quite effective in eliminating erroneous vote situations. The first is a unique identifier generated at the time of registration and given to the voter. After that, in the second level of security, when the voter presents his or her ID to an Election Commission Officer, the officer will crosscheck it, and now the new tier of verification, which the voter must go through, will greatly improve security by matching the voter ’s current facial features with those in the database, reducing the chances of false voting making the system safer and more accurate. We shall explore the many sorts of algorithms used in the field of face recognition in this study. In addition, we shall do a comparison between these methods. We also tested the correctness of these algorithms by putting them into practice and rating them on a test set.