  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.
