Abstract
This paper compares two methods for classification of Old Slavic letters. Traditional letter recognition programs cannot be applied on the Old Slavic Cyrillic manuscripts because these letters have unique characteristics. The first classification method is based on a decision tree and the second one uses fuzzy techniques. Both methods use the same set of features extracted from the letter bitmaps. Results from the conducted research reveal that discriminative features for recognition of Church Slavic Letters are number and position of spots in the outer segments, presence and position of vertical and horizontal lines, compactness and symmetry. The efficiency of the implemented classifiers is tested experimentally.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Scripta & e-Scripta. The Journal of Interdisciplinary Mediaeval Studies, vol. 6. Institute of Literature, Bulgarian Academy of Sciences. “Boyan Penev” Publishing Center (2008)
Mori, S., Suen, C.Y., Yamamoto, K.: Historical Review of OCR Research and Development. Proceedings of the IEEE 80, 1029–1058 (1992)
Vinciarelli, A.: A Survey on Off-line Cursive Word Recognition. Pattern Recognition 35, 1433–1446 (2002)
Kavallieratou, E., Fakotakis, N., Kokkinakis, G.: Handwritten Character Recognition Based on Structural Characteristics. In: 16th International Conference on Pattern Recognition, pp. 139–142 (2002)
Malaviya, A., Peters, L.: Fuzzy Handwriting Description Language: FOHDEL. Pattern Recognition 33, 119–131 (2000)
Eastwood, B., Jennings, A., Harvey, A.: A Feature Based Neural Network Segmenter for Handwritten Words. In: International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 1997), Australia, pp. 286–290 (1997)
Ntzios, K., Gatos, B., Pratikakis, I., Perantonis, S.J.: An Old Greek Handwritten OCR System based on an Efficient Segmentation-free Approach. Int. Journal on Document Analysis and Recognition 9(2), 179–192 (2007)
Chen, C.H., Curtins, J.: Word Recognition in a Segmentation-free Approach to OCR. In: Second International Conference on Document Analysis and Recognition (ICDAR 1993), pp. 573–576 (2003)
Antic, V.: Macedonian Medieval Literature. Institute for Macedonian Literature. Skopje, Macedonia (1997) (in Macedonian)
Atanasova, S.: Linguistic Analysis of Bitola’s Liturgical Book, Institute of Macedonian Language - Skopje, Macedonia (1990) (in Macedonian)
Velev, I., Makarijoska, L., Crvenkovska, E.: Macedonian Monuments with Glagolitic and Cyrillic Handwriting, Stip, Macedonia (August 2, 2008) (in Macedonian)
Russian Review of Cyrillic Manuscripts, http://xlt.narod.ru/pg/alpha.html
Klekovska, M., Nedelkovski, I., Stojcevska-Antic, V., Mihajlov, D.: Automatic Letter Style Recognition of Church Slavic Manuscripts. In: Proc. of 44th Int. Scientific Conf. on Information, Communication and Energy Systems and Technologies, Veliko Tarnovo, Bulgaria, pp. 221–224 (2009)
Cheriet, M., Kharma, N., Liu, C.L., Suen, C.Y.: Character Recognition Systems, A Guide for Students and Practioners. John Wiley and Sons, New Jersey (2007)
Martinovska, C., Nedelkovski, I., Klekovska, M., Kaevski, D.: Fuzzy Classifier for Church Slavic Handwritten Characters. In: Proc. of 14th Int. Conf. on Enterprise Information Systems, Wroclaw, Poland, pp. 310–313 (2012)
Yager, R.: On the Representation of Multi-Agent Aggregation using Fuzzy Logic. Cybernetics and Systems 21, 575–590 (1990)
Martinovska, C., Nedelkovski, I., Klekovska, M., Kaevski, D.: Recognition of Old Cyrillic Slavic Letters: Decion Tree versus Fuzzy Classifier Experiments. In: Yager, R.R., Sgurev, V., Hadjiski, M. (eds.) Proc. 6th IEEE Int. Conf. on Intelligent Systems 2012, Sofia, Bulgaria, vol. I, pp. 48–53 (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Klekovska, M., Martinovska, C., Nedelkovski, I., Kaevski, D. (2013). Comparison of Models for Recognition of Old Slavic Letters. In: Markovski, S., Gusev, M. (eds) ICT Innovations 2012. ICT Innovations 2012. Advances in Intelligent Systems and Computing, vol 207. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37169-1_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-37169-1_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37168-4
Online ISBN: 978-3-642-37169-1
eBook Packages: EngineeringEngineering (R0)