Open AccessRelationship between the Line Structured Light Vision Calibration Accuracy and Hardware Parameters
Author(s) -
Jinghe Zhao,
Qingchang Tan,
Bo Jiang,
Jing Hu,
Siyuan Liu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1881/2/022006
Subject(s) - calibration , computer vision , robustness (evolution) , artificial intelligence , computer science , structured light , accuracy and precision , line (geometry) , camera resectioning , machine vision , mathematics , statistics , biochemistry , chemistry , geometry , gene
The line structured light vision has better robustness and higher measurement accuracy as an active vision measurement method, which is widely used in the measurement of component size and shape tolerance. The calibration is a key technology of vision measurement. The calibration accuracy is not only affected by the calibration algorithm, but the parameters of the hardware equipment also have an important impact on the final calibration accuracy. Based on the analysis of the calibration algorithm, this paper conducts a theoretical analysis on the selection of the main hardware parameters, and uses the orthogonal experiment method to determine the relationship between the equipment parameters and the calibration accuracy. In the experiments, the aperture has the greatest impact on the calibration accuracy among the main equipment parameters, and the calibration accuracy is the highest when the camera aperture is between F4-F8.