Open AccessHigh-accuracy calibration of line-structured light vision sensor by correction of image deviation
Author(s) -
Xiao Pan,
Zhen Liu
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.27.004364
Subject(s) - structured light , calibration , planar , computer science , feature (linguistics) , computer vision , artificial intelligence , point (geometry) , vanishing point , image sensor , measurement uncertainty , line (geometry) , machine vision , compensation (psychology) , optics , mathematics , image (mathematics) , physics , psychology , linguistics , statistics , philosophy , computer graphics (images) , geometry , psychoanalysis
The structured-light vision sensor calibration approach based on planar target fails to generate reliable and accurate results due to the inaccurate localization of feature points in outdoor complex lighting environments. To address this issue, a novel high-accuracy calibration method that corrects image deviation is proposed for line-structured light vision sensor in this paper. The mathematical solution for stripe point location uncertainty is put forward and the location uncertainty of target feature points and stripe points is established. Moreover, the location deviation of all points is computed through large-scale nonlinear multi-step optimization based on the constraints of uncertainty. After compensation, the planar target based calibration method is adopted to solve the light plane equation. Both simulative and physical experiments have carried out to evaluate the performance of the proposed method and the results show that the proposed method is robust under large feature points localization deviation and can achieve the same measurement accuracy as the planar target calibration method under ideal imaging conditions, which reduces the requirements of the calibration environment, and has important practical engineering application value.