The paper presents a script classification method of the medieval documents originated from the Balkan region. It consists in a multi-step procedure which includes the text mapping according to typographical features, creation of equivalent image patterns, run-length pattern analysis in order to establish a feature vector and state-of-the art classification method Genetic Algorithms Image Clustering for Document Analysis (GA-ICDA) which successfully disseminates the documents written in different scripts. The proposed method is evaluated on custom oriented document databases, which include the handprinted or printed documents written in old Cyrillic, angular and round Glagolitic, ancient Latin and Greek scripts. The experiment demonstrates very good results.

Classification of the scripts in medieval documents from Balkan region by run-length texture analysis

Amelio A.;
2015-01-01

Abstract

The paper presents a script classification method of the medieval documents originated from the Balkan region. It consists in a multi-step procedure which includes the text mapping according to typographical features, creation of equivalent image patterns, run-length pattern analysis in order to establish a feature vector and state-of-the art classification method Genetic Algorithms Image Clustering for Document Analysis (GA-ICDA) which successfully disseminates the documents written in different scripts. The proposed method is evaluated on custom oriented document databases, which include the handprinted or printed documents written in old Cyrillic, angular and round Glagolitic, ancient Latin and Greek scripts. The experiment demonstrates very good results.
2015
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Inglese
22nd International Conference on Neural Information Processing, ICONIP 2015
2015
tur
9489
442
450
9
978-3-319-26531-5
978-3-319-26532-2
Springer Verlag
Classification; Historical document; Optical character recognition; Pattern recognition; Run-length statistics; Script identification
none
Brodic, D.; Amelio, A.; Milivojevic, Z. N.
273
info:eu-repo/semantics/conferenceObject
3
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11564/770256
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