Open AccessPhase-shifting profilometry for the robust 3-D shape measurement of moving objects
Author(s) -
Minghui Duan,
Yi Jin,
Chunmei Xu,
Xiaobo Xu,
Changan Zhu,
Enhong Chen
Publication year - 2019
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.27.022100
Subject(s) - computer vision , profilometer , artificial intelligence , computer science , absolute phase , phase (matter) , coordinate system , transformation (genetics) , pixel , phase correlation , structured light 3d scanner , motion estimation , optics , mathematics , physics , scanner , mathematical analysis , fourier transform , fourier analysis , biochemistry , chemistry , short time fourier transform , quantum mechanics , surface roughness , gene
Arbitrary two-dimensional (2-D) motion introduces coordinate errors and phase errors to three-dimensional (3-D) shape measurement of objects in phase-shifting profilometry (PSP). This paper presents a new robust 3-D reconstruction method for arbitrary 2-D moving objects by introducing an adaptive reference phase map and the motion estimation based on fence image. First, a composite fence image is used to track object motion. Second, to obtain the transformation matrixes and remove the coordinate errors among object images, the angle extraction technique and the 1-D hybrid phase correlation method (1-D HPCM) are integrated to automatically estimate the sub-pixel motion of objects. Third, the phase errors are compensated to obtain the rough absolute phase map of objects by combining the transformation matrixes with the reference phase map. Finally, the absolute phase map is refined to reconstruct the 3-D surfaces of moving objects with adaptive reference phase map. The proposed computational framework can accurately and automatically realize 3-D shape measurement of arbitrary objects with 2-D movement. The results of experiment verify the effectiveness of our computational framework.