Deciphering Historical Inscriptions Using Machine Learning Methods

Loránd Lehel Tóth (), Gábor Hosszú () and Ferenc Kovács ()
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Loránd Lehel Tóth: Budapest University of Technology and Economics
Gábor Hosszú: Budapest University of Technology and Economics
Ferenc Kovács: Budapest University of Technology and Economics

A chapter in LISS 2020, 2021, pp 419-435 from Springer

Abstract: Abstract This paper presents the results of a decipher historical inscriptions approach to demonstrate the application of different similarity metrics, classification and algorithm acceleration methods. Deciphering historical inscriptions is difficult in the most cases because the survived inscriptions typically contain calligraphic glyphs, grapheme errors or incomplete words. The basis of the presented methods are the geometric-topological features, which form feature vectors for each glyphs and undeciphered symbols that describes the shape of them with the numerical data. The elaborated method calculates the similarity distances of the inscriptions by the matching accuracies of the recognized graphemes through their topological feature vectors and determines the meaning of the inscription using an external dictionary of historical words. The actual version of the deciphering software is restricted for the one-word-long inscriptions. The article presents experimental results, which were processed on a real inscription. It demonstrates the efficiency of the methods. The deciphering software could be used for a paleographical research, especially in deciphering ancient hard to read inscriptions.

Keywords: Computational palaeography; Deciphering ancient inscriptions; Pattern recognition; Topological features; Scriptinformatics; Similarity metrics (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-33-4359-7_30

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DOI: 10.1007/978-981-33-4359-7_30

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