Model-based noise prediction for fringe projection systems - A tool for the statistical analysis of evaluation algorithms
Model-based noise prediction for fringe projection systems - A tool for the statistical analysis of evaluation algorithms
复制标题
DOI：
10.1515/teme-2016-0059
复制
发表时间：
2017-02-01
影响因子：
1
通讯作者：
Tutsch, Rainer
中科院分区：
文献类型：
--
作者：
Fischer, Marc;Petz, Marcus;Tutsch, Rainer
对于全场光学三维测量系统，在稳定和可控的环境下测量光学协作表面时，摄像机噪声是主要的不确定因素。在工业应用中，这种测量系统很少进行重复测量。这导致在随后的评估步骤中统计上不是最优的结果，因为丢失了关于单个测量点质量的重要信息。在这项工作中，这一信息将被证明可以通过基于模型的噪声预测来恢复用于相位测量的光学系统。对于条纹投影系统，该方法的能力将被示例性地演示，并且将表明，该方法确实能够为每个测量点产生由图像传感器噪声引起的空间随机偏差的单独估计。这为不同评估策略的统计表征和比较提供了一个有价值的工具，这在两个不同的三角测量过程中得到了示范。
For full-field optical 3D measurement systems, camera noise is the dominant uncertainty factor when optically cooperative surfaces are measured in a stable and controlled environment. In industrial applications repeated measurements are seldom executed for this kind of measurement systems. This leads to statistically suboptimal results in subsequent evaluation steps as the important information about the quality of individual measurement points is lost. In this work it will be shown that this information can be recovered for phasemeasuring optical systems with a model-based noise prediction. The capability of this approach will be demonstrated exemplarily for a fringe projection system and it will be shown that this method is indeed able to generate an individual estimate for the spatial stochastic deviations resulting from image sensor noise for each measurement point. This provides a valuable tool for a statistical characterization and comparison of different evaluation strategies, which is demonstrated exemplarily for two different triangulation procedures.