Open AccessPhase-3D mapping method developed from back-projection stereovision model for fringe projection profilometry
Author(s) -
Zewei Cai,
Xiaoli Liu,
Ameng Li,
Qijian Tang,
Xiang Peng,
Bruce Z. Gao
Publication year - 2017
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.25.001262
Subject(s) - structured light 3d scanner , projection (relational algebra) , calibration , profilometer , computer science , computer vision , artificial intelligence , reprojection error , phase (matter) , 3d reconstruction , point (geometry) , process (computing) , structured light , optics , algorithm , mathematics , physics , geometry , image (mathematics) , statistics , scanner , quantum mechanics , surface roughness , operating system
Two major methods for 3D reconstruction in fringe projection profilometry, phase-height mapping and stereovision, have their respective problems: the former has low-flexibility in practical application due to system restrictions and the latter requires time-consuming homogenous points searching. Given these limitations, we propose a phase-3D mapping method developed from back-projection stereovision model to achieve flexible and high-efficient 3D reconstruction for fringe projection profilometry. We showed that all dimensional coordinates (X, Y, and Z), but not just the height coordinate (Z), of a measured point can be mapped from phase through corresponding rational functions directly and independently. To determine the phase-3D mapping coefficients, we designed a flexible two-step calibration strategy. The first step, ray reprojection calibration, is to determine the stereovision system parameters; the second step, sampling-mapping calibration, is to fit the mapping coefficients using the calibrated stereovision system parameters. Experimental results demonstrated that the proposed method was suitable for flexible and high-efficient 3D reconstruction that eliminates practical restrictions and dispenses with the time-consuming homogenous point searching.