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Generalised, multilingual, optical Braille recognition models

Thesis (MSc)--Stellenbosch University, 2026.

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Bibliographic Details
Main Author: Van der Linden, Wicus Jan
Other Authors: Grobler, T. L.
Format: Thesis
Language:English
Published: Stellenbosch : Stellenbosch University 2026
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access_status_str Open Access
author Van der Linden, Wicus Jan
author2 Grobler, T. L.
author_browse Grobler, T. L.
Van der Linden, Wicus Jan
author_facet Grobler, T. L.
Van der Linden, Wicus Jan
author_sort Van der Linden, Wicus Jan
collection Thesis
dc_rights_str_mv Stellenbosch University
description Thesis (MSc)--Stellenbosch University, 2026.
format Thesis
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institution Stellenbosch University (South Africa)
language English
last_indexed 2026-06-10T12:41:24.431Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2026
publishDateRange 2026
publishDateSort 2026
publisher Stellenbosch : Stellenbosch University
publisherStr Stellenbosch : Stellenbosch University
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source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/135695 Generalised, multilingual, optical Braille recognition models Van der Linden, Wicus Jan Grobler, T. L. Van Zijl, L. Stellenbosch University. Faculty of Science. Dept. of Computer Science. Thesis (MSc)--Stellenbosch University, 2026. Van der Linden, W. J. 2026. Generalised, multilingual, optical Braille recognition models. Unpublished masters thesis. Stellenbosch: Stellenbosch University [online]. Available: https://scholar.sun.ac.za/items/1933f16b-1744-416c-8dc3-dc17ae39d157 Optical Braille recognition (OBR) is the computer vision task of extracting and classifying character cells from a Braille document. This study investigates the impact of class imbalance and adverse data quality conditions on OBR performance, by training standard multiclass (well adopted methodology) and novel multilabel (proposed in this work) models on different scenarios with resampled training data. These models are evaluated on unseen test data, both in-distribution and out-of-distribution, as well as on simulated adverse conditions. The results show that the proposed multilabel modelling approach outperforms the current standard multiclass approach across different evaluations. Multilabel models further generalise better than multiclass models to severe adverse data quality conditions, and achieve more stable performance across both majority and minority classes. Additionally, the use of data resampling to reduce imbalance in training data leads to improved performance generalisation, for both modelling approaches. In particular, a multi-objective resampling strategy minimising both the imbalance in character classes and the correlations between Braille dots, yields exceptionally stable performance across different conditions. In contrast, multiclass models trained on imbalanced, non-resampled data consistently exhibit poor generalisation to adverse conditions and minority Braille characters. In summary, these findings strongly support the conclusion that the application of the multilabel classification approach, in combination with strategic data resampling, yields robust OBR models exhibiting generalised performance across diverse Braille datasets. Masters 2026-04-08T07:53:44Z 2026-04-08T07:53:44Z 2026-03 Thesis https://scholar.sun.ac.za/handle/10019.1/135695 en Stellenbosch University 199 pages application/pdf Stellenbosch : Stellenbosch University
spellingShingle Van der Linden, Wicus Jan
Generalised, multilingual, optical Braille recognition models
title Generalised, multilingual, optical Braille recognition models
title_full Generalised, multilingual, optical Braille recognition models
title_fullStr Generalised, multilingual, optical Braille recognition models
title_full_unstemmed Generalised, multilingual, optical Braille recognition models
title_short Generalised, multilingual, optical Braille recognition models
title_sort generalised multilingual optical braille recognition models
url https://scholar.sun.ac.za/handle/10019.1/135695
work_keys_str_mv AT vanderlindenwicusjan generalisedmultilingualopticalbraillerecognitionmodels