Refraction error analysis in stereo vision for system parameters optimization

Abstract

The traditional stereo vision system with an air-based imaging model is unsuitable for multi-layer imaging conditions, where refraction effects can introduce significant errors in the measurement outcomes. Although numerous theoretical studies have developed refraction correction algorithms, it may be more beneficial and desirable to reduce the error by optimizing the system parameters in some cases. To address this dilemma, in this study, we first build a three-layer stereo vision model by forward projection and backward reconstruction. Then, the impact of various factors on the errors of reconstructed coordinates in the conditions of air-glass-air and air-glass-water is demonstrated through simulations. Real experiments are further carried out to verify the validity of the simulation. Finally, a practical guide for conducting experiments and tests is presented to assist in the design of more effective system parameters.