To add to that point, if you manage to get screenshots you can do an image comparison using perceptual hashing [0]. The idea is to compute hashes of images and

To add to that point, if you manage to get screenshots you can do an image comparison using perceptual hashing [0]. The idea is to compute hashes of images and compare those, rather than scanning through each pixel. Note that perceptual hashes should not obey the avalanche effect, so a minor difference in the two images should yield a small change in the hashes (desirable in this case). Then accept results that are within some small % error margin. An example of a library that does this is jimp [1]. [0] https://en.wikipedia.org/wiki/Perceptual_hashing https://en.wikipedia.org/wiki/Perceptual_hashing [1] https://github.com/oliver-moran/jimp#comparing-images https://github.com/oliver-moran/jimp#comparing-images