Accurate 3D Shape Reconstruction from Single Structured-Light Image via Fringe-to-Fringe Network
- Resource Type
- article
- Authors
- Hieu Nguyen; Zhaoyang Wang
- Source
- Photonics, Vol 8, Iss 11, p 459 (2021)
- Subject
- three-dimensional sensing
three-dimensional shape reconstruction
single-shot imaging
height measurements
depth measurements
deep learning
Applied optics. Photonics
TA1501-1820
- Language
- English
- ISSN
- 2304-6732
Accurate three-dimensional (3D) shape reconstruction of objects from a single image is a challenging task, yet it is highly demanded by numerous applications. This paper presents a novel 3D shape reconstruction technique integrating a high-accuracy structured-light method with a deep neural network learning scheme. The proposed approach employs a convolutional neural network (CNN) to transform a color structured-light fringe image into multiple triple-frequency phase-shifted grayscale fringe images, from which the 3D shape can be accurately reconstructed. The robustness of the proposed technique is verified, and it can be a promising 3D imaging tool in future scientific and industrial applications.