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Hand -Based Multimodal Biometric Authentication System

Publication Type : Conference Proceedings

Publisher : IEEE

Source : 2024 2nd International Conference on Artificial Intelligence and Machine Learning Applications Theme: Healthcare and Internet of Things (AIMLA)

Url : https://doi.org/10.1109/aimla59606.2024.10531351

Campus : Nagercoil

School : School of Computing

Year : 2024

Abstract : Biometric authentication technologies have become more well-known recently because of their high accuracy and security in validating individuals' identities. Finger's vein and knuckle biometrics are two of the most promising biometric modalities for personal identification. By combining the distinctive characteristics of both finger's vein and knuckle biometric recognition practices, this technology offers a revolutionary way to improve biometric security and accuracy. Finger-knuckle recognition is concerned with the shape and creases of the knuckles, whereas finger-vein technology examines the distinct vascular patterns found within each finger. The system overcomes individual constraints and improves security and accuracy by integrating these two methods. A fusion algorithm and an extensive dataset are developed by the proposed system for training and testing. This system may be used for access control and identity verification, as well as to increase security and decrease false acceptances. By advancing biometric authentication methods, this research promises a safer digital future.

Cite this Research Publication : Baratam Siddardha, S. Veluchamy, Hand -Based Multimodal Biometric Authentication System, 2024 2nd International Conference on Artificial Intelligence and Machine Learning Applications Theme: Healthcare and Internet of Things (AIMLA), IEEE, 2024, https://doi.org/10.1109/aimla59606.2024.10531351

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