Optical character recognition has gotten good enough to trust for everyday use, but the accuracy you get out of it still depends heavily on what goes in. A blurry photo taken at an angle will always read worse than a flat, well-lit scan, no matter how good the underlying engine is.
Lighting and angle matter more than resolution
A high-resolution photo taken at a steep angle, with shadows crossing the text, will often perform worse than a lower-resolution image shot straight-on in even light. Before running OCR, it's worth retaking the photo flat and well-lit if the first attempt looks distorted.
Printed text and handwriting need different handling
Standard OCR is trained on printed fonts — clean, consistent letterforms. Handwriting varies enormously from person to person, so it needs a model built specifically for it. Feeding a handwritten note into a printed-text OCR tool (or vice versa) is the most common reason results come back garbled.
Crop out anything that isn't text
Logos, photos, and decorative borders inside the same image as the text can confuse an OCR engine into trying to "read" them. Cropping tightly to just the text block before scanning usually improves accuracy more than any setting adjustment would.
Always proofread the output
Even accurate OCR occasionally swaps easily-confused characters (0/O, 1/l/I, rn/m). For anything that matters — a contract, an ID number, a phone number — a quick read-through of the extracted text against the original image catches these before they cause a real problem.
TeckForge's OCR — Image to Text and Handwriting to Text tools process images entirely in your browser, so scanned documents and handwritten notes never have to be uploaded anywhere to become editable text.
