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Structured Light Three-Dimensional Measurement Based on Machine Learning
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DOI：10.3390/s19143229.png)
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Abstract
En 中文
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%.
Keywords:
structured light
3D measurement
machine learning
LSSVM
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