Evaluating parametric uncertainty using non-linear regression in fringe projection
Evaluating parametric uncertainty using non-linear regression in fringe projection
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DOI：
10.1016/j.optlaseng.2022.107377
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发表时间：
2023-03
影响因子：
4.6
通讯作者：
George Gayton;Mohammed A. Isa;R. Leach
中科院分区：
文献类型：
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作者：
George Gayton;Mohammed A. Isa;R. Leach
光学坐标测量系统，如条纹投影系统，提供快速，高密度的测量任意表面形貌。条纹投影测量的多功能性、速度和信息密度使其作为现场测量设备和自主检测系统具有吸引力。然而，测量过程的复杂性使得评估条纹投影测量的不确定性变得复杂-即使在假设的简单情况下，其中测量的准确度仅受定义来自指示的测量的量的准确度的限制;在此命名为系统参数。本文通过验证一系列假设，给出了一种探讨条纹投影系统参数不确定性的方法。这项调查的结果意味着共同的失真模型（布朗-康拉迪模型）是不够具体的相机或投影仪的条纹投影系统，以评估其不确定度。
Optical coordinate measurement systems, such as fringe projection systems, offer fast, high-density measurements of arbitrary surface topographies. The versatility, speed and information density of fringe projection measurements make them attractive as in-situ measurement devices and autonomous inspection systems. However, the complex nature of the measurement process makes evaluating uncertainty from a fringe projection measurement complex – even in the hypothetical simple case where the accuracy of a measurement is limited only by the accuracy in the quantities that define a measurement from an indication; named system parameters here. In this paper, by validating a series of assumptions, a method to explore the uncertainty in the system parameters of a fringe projection system is given. The results of this investigation imply the common distortion model (the Brown-Conrady model) is not specific enough to the camera or projector of a fringe projection system to evaluate its uncertainty.