Passive binary defocusing for large depth 3D measurement based on deep learning.
Appl Opt
; 60(24): 7243-7253, 2021 Aug 20.
Article
em En
| MEDLINE
| ID: mdl-34613012
ABSTRACT
Phase-shifting profilometry (PSP) based on the binary defocusing technique has been widely used due to its high-speed capability. However, the required adjustment in projector defocus by traditional method is inaccurate, inflexible, and associated with fringe pitch. Instead of manual defocusing adjustment, a passive defocus of the binary patterns based on deep learning is proposed in this paper. Learning the corresponding binary patterns with a specifically designed convolutional neural network, high-quality three-step sinusoidal patterns can be generated. Experimental results demonstrate that the proposed method could reduce phase error by 80%-90% for different fringe pitches without projector defocus and outperform the traditional method by providing more accurate and robust results within a large measuring depth.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Appl Opt
Ano de publicação:
2021
Tipo de documento:
Article