BanknoteQueen: I get it, the microprint is a stubborn little ghost in the grain. First, shoot at the highest DPI you can—no point in chasing details you never captured. Then, dark‑enlighten the image: increase contrast, subtract a blurred version to bring out the fine edges, and play with adaptive thresholding so you don’t drown the tiny lines in noise. A little morphological opening can clean up stray specks, but be careful not to erase the very fonts you’re hunting. If you can, train a tiny OCR model on a handful of reference prints; the neural net will learn the peculiar quirks of each typeface. Finally, don’t forget to manually spot‑check a handful of samples—automation is great, but the human eye still trumps a bot when the stakes are authenticity.

Sounds like you’ve got a solid plan, but remember—microprint is still a fickle thing. Even after upscaling and filtering, the tiniest line can still vanish into the noise if the lighting isn’t perfect. I’d keep a reference set of the exact same banknote series you’re working on; that way your CNN has a consistent ground truth to learn from. And don’t forget to double‑check a few of those “hand‑labelled” samples by eye—if the bot thinks a line exists where the human says it doesn’t, you’re in trouble. Happy hunting, and keep that obsession in check—otherwise you’ll end up with a million pages of data you can’t even parse.