Accurate 3D measurements of complex geometry via modulation soft-edge prior

Minghui Duan; Ruihu Zhang; Yabing Zheng; Yi Jin; Jinjin Zheng

doi:10.1117/12.2666253

4 April 2023 Accurate 3D measurements of complex geometry via modulation soft-edge prior

Minghui Duan, Ruihu Zhang, Yabing Zheng, Yi Jin, Jinjin Zheng

Proceedings Volume 12617, Ninth Symposium on Novel Photoelectronic Detection Technology and Applications; 1261746 (2023) https://doi.org/10.1117/12.2666253
Event: 9th Symposium on Novel Photoelectronic Detection Technology and Applications (NDTA 2022), 2022, Hefei, China

Abstract

CNN-based fringe analysis has solved various challenging tasks in optical metrology. However, these CNN-based fringe analysis methods perform poorly in high-frequency features because low-frequency features dominate and are easy to learn. In this work, to fully extract the high-frequency features, we present a comparative analysis of off-the-shelf image edges, observing that these image edge priors fail to characterize the high-frequency component of the modulation image. Based on this, we propose fusing modulation soft-edge prior into the fringe analysis network for accurate 3D measurements of complex geometry. Instead of off-the-shelf image edges acquired by binarization preprocessing, the soft edge maximally preserves the modulation features while avoiding false modulation edges. The Soft-Edge Assisted Fringe Analysis (SEAFA) network can maintain high-quality overall measurements while improving the ability to extract the high-frequency component of complex geometry. Extensive experiments demonstrate that the SEAFA network can achieve more accurate 3D measurements than the previous CNN-based methods, especially for complex geometry.

Citation Download Citation

Minghui Duan, Ruihu Zhang, Yabing Zheng, Yi Jin, and Jinjin Zheng "Accurate 3D measurements of complex geometry via modulation soft-edge prior", Proc. SPIE 12617, Ninth Symposium on Novel Photoelectronic Detection Technology and Applications, 1261746 (4 April 2023); https://doi.org/10.1117/12.2666253

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