Motion blur
Blur can smear character strokes and cause the OCR engine to confuse letters. Burst capture and frame selection are possible countermeasures.
Research
Testing where camera OCR breaks.
VisoraAI can be evaluated by studying blur, glare, distance, preprocessing, and OCR accuracy. The goal is to connect real visual conditions with measurable recognition outcomes.
Glare
Reflections can erase strokes and reduce contrast. Detection can identify glare and trigger spoken guidance before OCR.
Character Error Rate
CER compares recognized characters with ground truth, making OCR changes measurable instead of subjective.
A useful research question connects the user problem to a measurable system behavior.
For example, burst stacking depth can be tested against OCR accuracy under controlled motion blur. That turns an accessibility problem into an experiment: how many frames help, when do they stop helping, and what tradeoff does the system make?