Circular Region of Interest before thresholding

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Hi! This problem is classical with global-threshold methods (like Otsu). It's a very difficult task, and to my knowledge, there is no general method to handle this case.

During my thesis, I developed an algorithm for binarization which was focused on text but you can try with your images here : demoFAIR.

As your images have a big amount of blur, I suggest you to use a very low value for K (for instance 0.07), or if you can try with images before you blurred them, it will probably have better results. Of course, I would be happy to give you more details if you think this method worth a try!

I would suggest you an adaptive threshold. It is computing a threshold on regions and it will eliminate the problems of shadows. There are two types: Gaussian and K-Means. I would suggest you to try both of them to see which is better for your case. Here is the documentation on python, and here is the documentation for C++, you did not mentioned what you need.