Martinovska, Cveta and Nedelkovski, Igor and Klekovska, Mimoza and Kaevski, Dragan (2012) Recognition of Old Cyrillic Slavic Letters: Decision Tree Versus Fuzzy Classifier Experiments. In: Proceedings of 2012 IEEE Sixth International Conference on Intelligent Systems. Catalog Number CFP12802-PRT, 1 . IEEE Conference Publishing, pp. 48-53. ISBN 978-1-4673-2277-5
Full text not available from this repository. (Request a copy)Abstract
In this paper we are comparing two methods for
classification of Old Slavic Cyrillic characters. Traditional
character recognition programs cannot be applied to the Old
Slavic Church manuscripts due to the specific characteristics of
these characters. The first classification method is based on a
decision tree and the second one uses a fuzzy classifier. Both
methods employ the same set of features extracted from the
characters bitmaps. The prototypes are obtained by applying the
logical operators on the samples of digitalized characters from
original manuscripts. As features for defining a particular
character we use number and position of spots in the outer
segments, presence and position of beams and columns in
horizontal and vertical segments respectively, compactness and
symmetry. The fuzzy classifier creates a prototype consisting of
fuzzy rules by means of fuzzy aggregation of character features.
The classifier based on a decision tree is realized by a set of rules.
During the creation of the classifier, several splitting measures
are tested. We have created an application that implements the
proposed classifiers and have experimentally tested their
efficiency. Experimental results show that both classifiers
correctly recognize about 50% of the characters. For 10% of the
samples both classifiers make the same error and for 11% of
characters the predicted character is incorrect and different.
| Item Type: | Book Section |
|---|---|
| Subjects: | Natural sciences > Computer and information sciences |
| Divisions: | Faculty of Computer Science |
| Depositing User: | Cveta Martinovska Bande |
| Date Deposited: | 06 Nov 2012 15:11 |
| Last Modified: | 06 Nov 2012 15:11 |
| URI: | https://eprints.ugd.edu.mk/id/eprint/527 |
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