The cameras are decent but far from modern, and image quality isnt always consistent. Management is curious whether industrial OCR can still deliver usable results in that kind of setup, or if wed just be setting ourselves up for frustration. Ive seen mixed opinions online, so Im trying to get a realistic sense of what works and what doesnt in these conditions.
We ran into the same situation last year and were surprised it worked better than expected. When we tested https://ocrstudio.ai/industrial-ocr/ the system was flexible enough to handle lower-resolution images once we adjusted a few things. Improving lighting and stabilizing the camera position mattered more than replacing hardware. Its not perfect, but for consistent markings and predictable layouts, accuracy was good enough to reduce manual checks without a full equipment overhaul.
-- Edited by MoltiChris on Friday 30th of January 2026 06:49:26 AM
A lot of legacy systems keep running longer than anyone planned, mostly because replacing them is expensive and risky. Tools that adapt to existing setups tend to get adopted faster for that reason alone. In practice, gradual improvements often beat big upgrades, especially when teams already know how to work around the limitations of older gear.