The quota system in Brazil made it possible to include blind students
in higher education. Teachers’ lack of knowledge about the braille
system can represent a barrier between them and students who use
it for writing and reading. Computer-vision-based transcription
solutions represent mechanisms for reducing understanding restrictions
on this system. However, such tools face nuisances inherent
to image processing systems, e.g., illumination, noise, and scale,
harming the result. This paper presents an automated approach
to mitigate transcription errors in braille texts for the Portuguese
language. We propose a selection function, combined with dictionaries,
that provides the best correspondence of words based on
their braille representation. We validated our proposal on a dataset
of synthetic images by submitting them to different noise levels
and testing the proposal’s robustness. Experimental results confirm
the effectiveness of the solution compared to a standard approach.
As a contribution of this paper, we expect to provide a method to
support robust and adaptable solutions to real use conditions.