Iris Recognition for Voting System Using Machine Learning

This research demonstrates the feasibility and effectiveness of iris recognition technology for secure voting applications. Our system achieves 94.2% recognition accuracy while maintaining processing speeds suitable for practical electoral use. The combination of computer vision techniques and deep learning algorithms provides a robust foundation for biometric voter authentication. The security advantages offered by iris recognition, including fraud resistance and non-repudiation capabilities, address many vulnerabilities present in traditional voting systems. The contactless and non-invasive nature of iris capture enhances user acceptance while maintaining high security standards. Future research directions include exploring multi-modal biometric approaches, implementing advanced security features such as liveness detection, and optimizing system performance for larger-scale deployments. As democratic societies continue to face challenges related to voting system integrity, biometric authentication technologies like iris recognition offer promising solutions that can help preserve the fundamental principles of fair and secure elections

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