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Open AccessArticle

Structured Light Three-Dimensional Measurement Based on Machine Learning

Key Laboratory of Luminescence and Optical Information of Ministry of Education, Beijing Jiaotong University, Beijing 100044, China
Author to whom correspondence should be addressed.
Sensors 2019, 19(14), 3229;
Received: 6 May 2019 / Revised: 15 July 2019 / Accepted: 20 July 2019 / Published: 23 July 2019
(This article belongs to the Section Physical Sensors)
The three-dimensional measurement of structured light is commonly used and has widespread applications in many industries. In this study, machine learning is used for structured light 3D measurement to recover the phase distribution of the measured object by employing two machine learning models. Without phase shift, the measurement operational complexity and computation time decline renders real-time measurement possible. Finally, a grating-based structured light measurement system is constructed, and machine learning is used to recover the phase. The calculated phase of distribution is wrapped in only one dimension and not in two dimensions, as in other methods. The measurement error is observed to be under 1%. View Full-Text
Keywords: structured light; 3D measurement; machine learning; LSSVM structured light; 3D measurement; machine learning; LSSVM
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Zhong, C.; Gao, Z.; Wang, X.; Shao, S.; Gao, C. Structured Light Three-Dimensional Measurement Based on Machine Learning. Sensors 2019, 19, 3229.

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