Feature Selection for Classification of Old Slavic Letters

Martinovska Bande, Cveta and Klekovska, Mimoza and Nedelkovski, Igor and Kaevski, Dragan (2014) Feature Selection for Classification of Old Slavic Letters. Journal of Control Engineering and Applied Informatics, 16 (4). pp. 81-90. ISSN 1454-8658

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Official URL: http://ceai.srait.ro/index.php/ceai/article/view/2...

Abstract

This paper describes methodology for extracting discriminative features for fuzzy classification of Old Slavic characters. Recognition process is based on structural and statistical features, such as number and position of spots in outer segments, presence and position of horizontal and vertical lines and holes, compactness and symmetry. Preprocessing is divided into the following steps: conversion to black and white bitmaps, normalization, contour extraction and segmentation. Features are extracted from contour profiles, histograms and character intersections. C4.5 decision trees are used for feature selection. The same feature set is appropriate for different Old Slavic Cyrillic alphabets because of the similarity of their graphemes. The classification accuracy and precision are tested on Old Macedonian manuscripts and the decision trees are created for two alphabets Macedonian and Bosnian. The main advantage of the proposed method is saving processing resources and eliminating the need of large training sets necessary for Bayesian classifiers or neural networks.

Item Type: Article
Subjects: Natural sciences > Computer and information sciences
Divisions: Faculty of Computer Science
Depositing User: Cveta Martinovska Bande
Date Deposited: 25 Dec 2014 14:26
Last Modified: 25 Dec 2014 14:26
URI: http://eprints.ugd.edu.mk/id/eprint/11787

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