International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 05 | May 2023
p-ISSN: 2395-0072
www.irjet.net
A Novel Method for Facial Recognition Based Smart Voting System Using Machine Learning Sakshi1, Heena Kousar2, Madhumati3, Pooja T R4, Asst.Prof. Shaeista Begum5 1-4
Students, Dept. of Computer Science and Engineering ,Government Engineering College, Raichur ,Karnataka , India 5 Asst. Professor ,Dept. of Computer Science and Engineering ,Government Engineering College, Raichur ,Karnataka, India -------------------------------------------------------------------------***---------------------------------------------------------------------
Abstract
The proposed system has several advantages over traditional voting systems, such as improved accuracy, security, and speed. The use of facial recognition technology reduces the chances of human errors and prevents voter fraud, ensuring a fair and transparent voting process. The system is also faster than traditional voting systems, as the verification and authentication process is automated.
This paper presents a novel method for implementing a facial recognition-based smart voting system using machine learning. The proposed method involves the use of a facial recognition algorithm that is trained using deep learning techniques to recognize the faces of registered voters. The system is designed to improve the accuracy, security, and speed of the voting process. The system incorporates additional security measures, such as the use of biometric data, real-time monitoring, and a one-time password (OTP) for voter verification, to prevent voter fraud. The proposed method was evaluated using a dataset of pre-registered voters, achieving an accuracy rate of 98% in recognizing the faces of registered voters. The system has the potential to revolutionize the way we conduct elections, ensuring a fair and transparent voting process.
2. Related Works Article [1] "Facial Recognition-based Voting System" by V. R. Geetha and P. Lakshmi. This paper proposes a facial recognition-based voting system that uses machine learning to authenticate voters. The proposed system uses facial recognition algorithms to match the voter's face with the pre-registered images in the database. The system also includes additional security measures such as real-time monitoring and biometric data to prevent voter fraud.
Key Words: Facial recognition, machine learning,
Article [2] "A Face Recognition-Based Electronic Voting System Using Neural Networks" by M. Osman Tokhi, J. Ghaderi, and M. E. El-Tarhuni. This paper presents a face recognition-based electronic voting system using neural networks. The system uses a neural network to recognize the face of the voter and authenticate their identity. The system also includes additional security measures such as encryption and decryption techniques to ensure the integrity of the voting process.
smart voting system, deep learning, biometric data, voter fraud.
1. INTRODUCTION The traditional method of conducting elections involves a lengthy process of verification, authentication, and manual counting, which is often time-consuming and susceptible to human errors and fraud. The use of facial recognition technology in the field of voting has gained significant attention in recent years due to its potential to improve the accuracy and security of the voting process. In this paper, we propose a novel method for implementing a facial recognition-based smart voting system using machine learning.
Article [3] "A Secure and Efficient Face Recognition Based Electronic Voting System" by J. R. Jena and S. Panda. This paper proposes a secure and efficient face recognitionbased electronic voting system. The system uses a combination of facial recognition algorithms and machine learning techniques to authenticate voters. The system also includes additional security measures such as biometric data and real-time monitoring to prevent voter fraud.
The proposed method involves the use of a facial recognition algorithm that is trained using deep learning techniques to recognize the faces of registered voters. The system captures the image of the voter's face and compares it to the pre-registered images in the database. If the face matches, the voter is allowed to cast their vote. The system also incorporates additional security measures, such as the use of biometric data, real-time monitoring, and a one-time password (OTP) for voter verification, to prevent voter fraud.
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Impact Factor value: 8.226
Article [4] "Facial Recognition-Based Voting System Using Convolutional Neural Networks" by Y. Yan and W. Zhang. This paper proposes a facial recognition-based voting system that uses convolutional neural networks (CNNs) to authenticate voters. The system uses a CNN to recognize the face of the voter and match it with the pre-registered images in the database. The system also includes additional
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