Camera Fingerprint

Camera fingerprinting leverages unique, inherent characteristics of imaging devices to identify their source, serving purposes like image authentication, forensic analysis, and model protection. Current research focuses on improving fingerprint robustness against distortions (e.g., using deep learning for distortion field regression) and developing efficient methods for fingerprint extraction and comparison, including techniques based on sensor noise patterns (PRNU), neural networks, and generative adversarial networks (GANs). These advancements have implications for combating misinformation, securing digital content, and enhancing various image processing applications.