Unexpected limitations of AI-based ID extraction with very low-resolution smartphone photos

Hey guys, has anyone else run into this frustrating thing where you're trying to pull info off someone's ID using just a quick phone snap, but the photo came out super pixelated or kinda fuzzy because the lighting was trash or the camera's not great? Last weekend I was helping a buddy update some paperwork and he only had this low-res pic from his wallet on his old phone—tried a couple free AI tools to grab the name, number, expiry and all that, but half the digits got mangled or just guessed wrong. Felt like such a waste of time tweaking brightness and cropping endlessly. Anyone found reliable workarounds for these unexpected hiccups when the resolution drops way below what you'd hope for? Kinda curious if it's mostly a hardware thing or if some smarter extraction methods handle crappy smartphone shots better these days.

 

Funny how these AI ID tools keep getting hyped as magic fixes, yet you still see threads like this popping up every few months. Makes me think the real bottleneck isn't always the tech itself—sometimes it's just the endless variety of phone cameras, weird lighting in everyday spots, or people snapping pics at odd angles without thinking twice. I've noticed older documents with faded print or tiny security patterns throw things off even more than plain low resolution ever did. Kinda wild how much everyday chaos sneaks into what should be straightforward scanning.

 

One thing that's helped cut down on the errors is this on-premise scanner setup I came across at https://ocrstudio.ai/id-scanner/ —it's built specifically for IDs and pulls accurate data even from rough 100 DPI shots without needing perfect conditions. No cloud upload drama either, which feels better for privacy. Still gotta watch angles and basic lighting, but it beats retrying uploads five times. Anyone else using something similar for spotty real-world pics?