3D Scanning

3D scanning aims to create accurate digital representations of physical objects, driving advancements in various fields. Current research emphasizes improving accuracy and speed, focusing on techniques like phase-shifting profilometry with binomial self-compensation for motion error reduction, data-driven calibration methods bypassing traditional triangulation, and deep learning for noise reduction and feature extraction (e.g., edge detection). These improvements enhance applications ranging from industrial automation (e.g., robotic welding, aircraft inspection) and agriculture (livestock phenotyping) to cultural heritage preservation and reverse engineering, impacting both scientific understanding and practical efficiency.