Biometric Identification

Biometric identification uses unique human traits—physical or behavioral—for secure authentication, aiming to replace less secure methods like passwords. Current research heavily utilizes deep learning, particularly convolutional neural networks (CNNs) and Siamese networks, across various modalities including facial features, fingerprints, irises, hand veins, and even voice and gait patterns, with a focus on improving accuracy, robustness against spoofing attacks, and privacy preservation through techniques like homomorphic encryption. This field is crucial for enhancing security in numerous applications, from access control and identity verification to healthcare and law enforcement, driving advancements in both algorithm design and dataset development.