MSc Project repo for computer vision star identification and satellite orientation project (CURRENTLY ACTIVE)
Please see a short explanatory video on YouTube.
Additionally, this tutorial is a really useful beginner's guide to OpenCV classifier training.
Contents so far:
- Stellarium scripts used to capture thousands of images from Stellarium in order to be processed into negative image datasets for machine learning training.
- Zipped folders containing negative image datasets, as well as bg.txt files, and python programs used to create these.
- Python programs used to create the positive images used for cascade training.
- Image files of the fiducial markers applied to starfields, to identify the patterns of bright stars that the machine learning relies upon for the identification.
- A sample set of 31 trained cascades for the northern celestial hemisphere.
- Python programs used to test the trained cascades against a supplied starfield image.
As of 19/08/19, I have finished working on this project as part of my University course. I hope to be able to spend further time on it as a hobby in order to keep developing the system, there are lots of improvements and additions I would like to have time to make. I hope that this repository may be of use to someone, and if you have questions please contact me, I will continue to monitor and work on this project. The best source of reference here is my MSc Thesis itself, which can be found above.