Enhanced 3D imaging accuracy using curved sensors: a simulation-based approach

Abstract

Abstract Three-dimensional (3D) modeling is a key requirement in computer vision, yet achieving high-speed and high-quality image acquisition remains challenging. Flat image sensors, commonly used in 3D scanners, suffer from edge blurring due to misalignment between the sensor plane and the curved focal surface of the lens. While complex lens designs can mitigate this issue, they increase manufacturing costs, weight, and optical distortions. This study investigates the advantages of curved sensors in improving imaging performance. Through software-based modeling and simulation, the study compares curved and flat sensors by analyzing key optical errors, including astigmatism, distortion, spherical aberration, and coma. The results indicate that curved sensors significantly enhance image quality and measurement accuracy. Notably, measurement errors are reduced by 44.68% compared to flat sensors. The findings highlight curved sensors as a promising alternative for high-precision 3D imaging, offering improved edge detection and dimensional measurement accuracy while reducing optical distortions.