A new publishing related to SVM method on OCR case, "Optical character recognition system for Baybayin scripts using support vector machine" - https://peerj.com/articles/cs-360/
Thanks for citation that to have more clearer that the method could work in some other cases.
This part is delight me and remind it back.
Abstract (of the paper)
In 2018, the Philippine Congress signed House Bill 1022
declaring the Baybayin script as the Philippines’ national writing
system. In this regard, it is highly probable that the Baybayin and
Latin scripts would appear in a single document. In this work, we
propose a system that discriminates the characters of both scripts. The
proposed system considers the normalization of an individual character
to identify if it belongs to Baybayin or Latin script and further
classify them as to what unit they represent. This gives us four
classification problems, namely: (1) Baybayin and Latin script
recognition, (2) Baybayin character classification, (3) Latin character
classification, and (4) Baybayin diacritical marks classification. To
the best of our knowledge, this is the first study that makes use of
Support Vector Machine (SVM) for Baybayin script recognition. This work
also provides a new dataset for Baybayin, its diacritics, and Latin
characters. Classification problems (1) and (4) use binary SVM while (2)
and (3) apply the multiclass SVM classification. On average, our
numerical experiments yield satisfactory results: (1) has 98.5%
accuracy, 98.5% precision, 98.49% recall, and 98.5% F1 Score; (2) has
96.51% accuracy, 95.62% precision, 95.61% recall, and 95.62% F1 Score;
(3) has 95.8% accuracy, 95.85% precision, 95.8% recall, and 95.83% F1
Score; and (4) has 100% accuracy, 100% precision, 100% recall, and 100%
F1 Score.
