Paper
10 February 2017 Parallel computing for fast and accurate phase analysis of fringe pattern by two-dimensional phase shifting methods
Author Affiliations +
Proceedings Volume 10250, International Conference on Optical and Photonics Engineering (icOPEN 2016); 102502Q (2017) https://doi.org/10.1117/12.2266693
Event: Fourth International Conference on Optical and Photonics Engineering, 2016, Chengdu, China
Abstract
Phase analysis techniques of fringe patterns have been widely used for noncontact three-dimensional shape and deformation measurement by the fringe projection method. Recently, we developed two novel accurate phase analysis methods. One is the two-dimensional sampling moiré method to perform robust phase analysis for a single-shot fringe pattern. The other is the two-dimensional spatiotemporal phase-shifting method to analyze phase distribution accurately for multi-step phase-shifted fringe patterns. To perform accurate phase analysis under low signal-to-noise ratio conditions, both the above two methods use the two-dimensional discrete Fourier transform or fast Fourier transform. Therefore, these algorithms are computationally expensive compared with the conventional one-dimensional sampling moiré and phase-shifting methods. In this study, a fast parallelization implementation for two-dimensional phase-shifting methods, including the two-dimensional sampling moiré method and the spatiotemporal phase-shifting method, are presented by utilizing multi-core CPU. Simulation and experimental results demonstrate that phase analysis can reach 7.5 and 5.9 times faster by use of a 12-core CPU compared with a single CPU.
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Shien Ri, Qinghua Wang, and Hiroshi Tsuda "Parallel computing for fast and accurate phase analysis of fringe pattern by two-dimensional phase shifting methods", Proc. SPIE 10250, International Conference on Optical and Photonics Engineering (icOPEN 2016), 102502Q (10 February 2017); https://doi.org/10.1117/12.2266693
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KEYWORDS
Fringe analysis

Phase shifts

Image processing

Parallel computing

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