Three-Dimensional Reconstruction of Macrotexture and Microtexture Morphology of Pavement Surface Using Six Light Sources–Based Photometric Stereo with Low-Rank Approximation

Abstract

Inadequate skid resistance of pavement surface is a substantial reason for traffic accidents. There is a close relationship between sliding resistance and characteristics of texture morphology, demanding high precision and comprehensive acquisition of both macrotexture and microtexture morphology. The traditional three light sources photometric stereo method is improved in this study fourfold. First, six light sources are adopted to enhance the illumination and eliminate incomplete information retrieval of pavement surface image. Second, a low-rank approximation is proposed in the image processing stage to significantly reduce the interference of noise, highlights, and shadow, resulting in a higher precision of reconstructed pavement surface compared with the existing photometric stereo method using three light sources. Third, unlike the control point–based weighting algorithm, a control point–based surface interpolation algorithm is established, which can further optimizes the precision of the reconstructed surface by combining the effect of global integration with the elevation of positions of relative points. Under testing in indoor conditions, a surface interpolation photometric stereo method with 2,500 control points and using low-rank approximation can effectively measure both macrotexture and microtexture morphology. Last, low-rank approximation and global integration with six light sources is used to relax the requirement of the surface interpolation photometric stereo method on control points. Statistical analysis indicates that low-rank approximation and global integration with six light sources can be an effective method for reconstructing three-dimensional (3D) macrotexture and microtexture morphology.