Fingerprint Recognition

Fingerprint recognition, aiming to reliably authenticate individuals based on their unique fingerprint patterns, is a mature yet actively researched field. Current research focuses on improving accuracy and robustness by addressing challenges like partial fingerprints, image quality degradation (e.g., due to skin distortion, moisture), and demographic biases in performance. This involves developing advanced algorithms, often based on convolutional neural networks (CNNs) and vision transformers (ViTs), for tasks such as feature extraction, distortion field estimation, and presentation attack detection. The ongoing advancements in fingerprint recognition have significant implications for security, forensics, and various applications requiring reliable biometric authentication.