Online Voting System

Abstract

In a rapidly digitizing world, the need for secure, transparent, and efficient voting systems is more critical than ever. Traditional voting systems, such as those using Electronic Voting Machines (EVMs) or paper ballots, suffer from various vulnerabilities including impersonation, duplicate voting, and human error during voter verification. This project introduces an advanced facial recognition-based voting system integrated with Aadhar authentication, aimed at resolving these issues. The system captures an individual's facial features using a webcam and stores these images along with their Aadhar number. Using the OpenCV library for face detection and a K-Nearest Neighbours (KNN) classifier for recognition, the system verifies the voter in real-time before allowing them to cast a vote.

This system consists of two main modules: the registration module and the voting module. During registration, a person’s face is captured multiple times and stored as a dataset. During voting, the same facial recognition system verifies the user’s identity. If authenticated and not already marked as voted, the system allows a single vote to be cast. The vote is logged along with the Aadhar number, party selected, date, and timestamp. Voice feedback confirms the successful recording of the vote, providing a user-friendly experience.