SMART VOTING SYSTEM THROUGH FACE RECOGNITION

Elections are a critical component of democratic governance, yet traditional voting systems continue to face significant challenges such as voter impersonation, duplicate voting, manual verification errors, and lack of transparency.These issues undermine public trust and election integrity.To overcome these limitations, this paper presents an offline Smart Voting System through Face Recognition that employs deep learning-based biometric authentication for secure and reliable voter verification.The proposed system performs voter registration using Aadhaar as a unique identifier and captures multiple facial samples through a webcam.Facial embeddings are extracted using a pre-trained deep learning model and stored locally using serialized pickle files.During the voting phase, real-time facial recognition is performed using cosine similarity, enhanced by temporal smoothing and face tracking to improve accuracy and stability.Votes are recorded securely in CSV format, ensuring transparency and preventing duplicate voting.Experimental evaluation demonstrates high recognition accuracy, low false acceptance rates, and efficient real-time performance, making the system suitable for secure offline voting environments.