BRAS: Bidirectional Reflectance Adjustment Strategy for 3-D Reconstruction of Mirror-Like Surface
Zheng Sun, Ben Wang, Yabing Zheng, Minghui Duan, Xin Fan, Yi Jin, Jinjin Zheng
Abstract
A mirror-like surface (MLS) reflects highlight, aggravating the image saturation in structured light 3-D reconstruction systems and precluding defect detection based on reconstructed 3-D profiles. Previous studies have focused on a strategy of limiting the luminous flux entering the camera. However, the high intensity of the reflected highlight forces the limitation to be strengthened, which heavily reduces the modulation in the images for the 3-D reconstruction. Therefore, we propose a new strategy to adjust the source of the reflected highlight, i.e., the bidirectional reflectance (BR) of the MLS, which fundamentally suppresses the highlight and removes the limitation on the luminous flux. To execute the proposed strategy, an unfixed view structured light system (UVSLS) is established. The UVSLS converts the reflection viewer from the real camera to the virtual camera, realizing the flexible adjustment of the MLS BR. Finally, an MLS 3-D reconstruction framework is constructed to obtain the 3-D profile of the MLS. Experiments demonstrate that the proposed framework reduces the saturated pixels by 73.72% compared with the conventional method. Compared with the previous methods, the saturated pixels are reduced by an average of 47.62%.