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https://github.com/helleb0re/structured-light-python
https://github.com/helleb0re/structured-light-python
baumer opencv optics physics python structured-light structured-light-for-3d-scanning
Last synced: 6 days ago
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- Host: GitHub
- URL: https://github.com/helleb0re/structured-light-python
- Owner: helleb0re
- Created: 2022-06-28T09:16:48.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-10-30T08:15:00.000Z (about 1 year ago)
- Last Synced: 2023-12-19T16:04:28.184Z (11 months ago)
- Topics: baumer, opencv, optics, physics, python, structured-light, structured-light-for-3d-scanning
- Language: Python
- Homepage:
- Size: 104 KB
- Stars: 4
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# **Structured light project**
This project is an attempt to create an easy-to-understand and flexible-to-use framework for implementing the Fringe Projection Profilometry (FPP) method in the Python.
## **Implementation**
* Ability to use any camera (modules with webcams through OpenCV and Baumer cameras through NeoAPI are implemented in the project)
* The Phaseshift Projection Profilometry (PSP) method with sinusoidal fringes is implemented to obtain phase fields
* Projection pattern generation supports an arbitrary number of phase shifts and an arbitrary number of periods
* A hierarchical approach is used to unwrap the phase fields
* Implemented automatic detection of the fringe projection area on the images (ROI)
* A simple gamma correction method for projected images is implemented
* Flexible adjustment of the experiment and hardware parameters with the help of config files
## **How to use**
1. Install depedicies
```
pip install opencv-contrib-python numpy scipy matplotlib
```
2. Setting the parameters of the experiment and the hardware in the file `config.py`
3. Launch main module
```
python main.py
```
In the script `examples/test_plate_phasogrammetry.py` there is an example of processing the results of the experiment to determine the shape of the surface of a granite slab using the phasogrammetric approach. To date, the measurement accuracy of about **60 µm** has been achieved.
## **References**
The following sources were used to implement the algorithms
[Zuo C. et al. Phase shifting algorithms for fringe projection profilometry: A review // Optics and Lasers in Engineering. 2018. Vol. 109. P. 23-59.](https://doi.org/10.1016/j.optlaseng.2018.04.019)
[Zuo C. et al. Temporal phase unwrapping algorithms for fringe projectionprofilometry: A comparative review // Optics and Lasers in Engineering. 2016. Vol. 85. P. 84-103.](https://doi.org/10.1016/j.optlaseng.2016.04.022)
[Feng S. et al. Calibration of fringe projection profilometry: A comparative review // Optics and Lasers in Engineering. 2021. Vol. 143. P. 106622.](https://doi.org/10.1016/j.optlaseng.2021.106622)
[Zhong K. et al. Pre-calibration-free 3D shape measurement method based on fringe projection // Optics Express. 2016. Vol. 24. №. 13. P. 14196-14207.](https://doi.org/10.1364/OE.24.014196)
## **Authors**
Anton Poroykov, Ph.D., associated professor
Nikita Sivov, graduate student
## **Acknowledgements**
The research was carried out at the expense of the grant Russian Science Foundation No. 22-21-00550 (https://rscf.ru/project/22-21-00550/).