Graduate Institute of Automation Technology, College of Mechanical & Electrical Engineering, No. 1, Section 3, National Taipei University of Technology, Zhong-Xiao E. Rd, Da'an District, Taipei City 10608, Taiwan.
Department of Mechanical Engineering, National Taiwan University, No. 1, Section 4, Roosevelt Rd, Da'an District, Taipei City 10617, Taiwan.
Sensors (Basel). 2019 Oct 28;19(21):4683. doi: 10.3390/s19214683.
In a multifrequency phase-shifting (MFPS) algorithm, the temporal phase unwrapping algorithm can extend the unambiguous phase range by transforming the measurement range from a short fringe pitch into an extended synthetic pitch of two different frequencies. However, this undesirably amplifies the uncertainty of measurement, with each single-frequency phase map retaining its measurement uncertainty, which is carried over to the final unwrapped phase maps in fringe-order calculations. This article analyzes possible causes and proposes a new absolute depth measurement algorithm to minimize the propagation of measurement uncertainty. Developed from normalized cross-correlation (NCC), the proposed algorithm can minimize wrong fringe-order calculations in the MFPS algorithm. The experimental results demonstrated that the proposed measurement method could effectively calibrate the wrong fringe order. Moreover, some extremely low signal-to-noise ratio (SNR) regions of a captured image could be correctly reconstructed (for surface profiles). The present findings confirmed measurement precision at one standard deviation below 5.4 µm, with an absolute distance measurement of 16 mm. The measurement accuracy of the absolute depth could be significantly improved from an unacceptable level of measured errors down to 0.5% of the overall measuring range. Additionally, the proposed algorithm was capable of extracting the absolute phase map in other optical measurement applications, such as distance measurements using interferometry.
在多频移相（MFPS）算法中，时间相位解缠算法可以通过将测量范围从短条纹间距转换为两个不同频率的扩展合成间距来扩展无歧义相位范围。然而，这会不期望地放大测量的不确定性，每个单频相位图保留其测量不确定性，这会在条纹顺序计算中传递到最终解缠相位图。本文分析了可能的原因，并提出了一种新的绝对深度测量算法来最小化测量不确定性的传播。所提出的算法源自归一化互相关（NCC），可以最小化 MFPS 算法中的错误条纹顺序计算。实验结果表明，所提出的测量方法可以有效地校准错误的条纹顺序。此外，还可以正确重建捕获图像的某些极低信噪比（SNR）区域（用于表面轮廓）。本研究结果证实了在 16 毫米的绝对距离测量下，测量精度在标准偏差以下 5.4 µm 时达到一个标准差。绝对深度的测量精度可以从不可接受的测量误差水平显著提高到总测量范围的 0.5%。此外，该算法还可以提取其他光学测量应用中的绝对相位图，例如使用干涉测量的距离测量。
