Uncertainty modeling and evaluation of profile measurement by structured light scanner

Abstract

Abstract A structured light scanner is mainly used to collect three-dimensional (3D) data of an object; however, the uncertainty evaluation of a specific measurement task is not perfect. This study discusses the source of the uncertainty component of the measurement system of a structured blue-light scanner, including the instrument itself, data acquisition, data processing, and other factors. Using the surface profile as the evaluation object, PolyWorks software was used to perform the data processing of the point cloud denoising, splicing, and registration. An uncertainty evaluation is performed based on the black-box evaluation model. The experimental results show that the uncertainty components introduced by the point cloud stitching and point cloud registration are the main components of the entire measurement system. The bootstrap method does not need to consider the probability distribution type of the error sources, which improves computational efficiency. This method has several advantages when the distribution state is unknown. This work is conducive to improving the task-oriented uncertainty evaluation of 3D scanners.