Exploring the Landscape: A Comprehensive Survey on Biometric-Based Identification System

Abstract In response to the rapid rise of electronic crimes, establishing a robust user authentication system has become imperative for access control and safeguarding private data. Human biometrics, including face, fingerprint, palm, iris scanning, facial features, signature, and voice, furnish a reliable security level for both personal and public utilization, surpassing traditional methods like passwords. This paper explores biometric identification systems, addressing techniques. It briefly reviews various modalities, analyzing their strengths and limitations. The examination extends to identification methods, covering feature extraction, matching algorithms, and performance evaluation parameters are discussed, emphasizing recent advancements like multi-modal biometrics and deep learning. The paper concludes with future research directions in biometric identification systems, including developing more accurate and robust techniques, improving data quality, and addressing ethical and legal issues. Keywords: Statistics; Data science; Biometrics; Capitalize the first word of each keyword.