Printed Arabic Characters Classification using A Statistical Approach
DOI:
https://doi.org/10.24297/ijct.v3i1a.2719Keywords:
Freeman chain coding, character recognition, feature extraction, classification.Abstract
In this paper, we propose simple classifiers for printed Arabic characters based on statistical analysis. 109 printed Arabic character images are created for each one of transparent, simplified and traditional Arabic fonts. Images are preprocessed by the binarization and followed by sequence of morphological operations. A non-linear filter is applied on the thinned ridge map to extract termination and bifurcation features. The thinned ridge map vectors (TRMVs) are created using a freeman chain code template. The spatial distribution and statistical properties of the extracted features are calculated.Downloads
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Published
2012-08-01
How to Cite
Zaqout, I. (2012). Printed Arabic Characters Classification using A Statistical Approach. INTERNATIONAL JOURNAL OF COMPUTERS &Amp; TECHNOLOGY, 3(1), 1–5. https://doi.org/10.24297/ijct.v3i1a.2719
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Section
Research Articles