Abstract
The paper proposed an algorithm for script discrimination using adjacent local binary patterns (ALBP). In the first stage, each letter is modeled according to its height. The real data are extracted from the probability distribution of the letter heights. Then, the gray scale co-occurrence matrix is computed. It is used as a starting point for the feature extraction. The extracted features are classified according to ALBP. Because of the variety in script characteristics, the statistical analysis shows the differences between scripts. Accordingly, the linear discrimination function is proposed to distinct the scripts. The proposed method is tested on the samples of the printed documents, which include Cyrillic and Glagolitic script. The results of experiments are encouraging.
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Brodić, D., Maluckov, Č.A., Milivojević, Z.N., Draganov, I.R. (2014). Differentiation of the Script Using Adjacent Local Binary Patterns. In: Agre, G., Hitzler, P., Krisnadhi, A.A., Kuznetsov, S.O. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2014. Lecture Notes in Computer Science(), vol 8722. Springer, Cham. https://doi.org/10.1007/978-3-319-10554-3_15
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DOI: https://doi.org/10.1007/978-3-319-10554-3_15
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10553-6
Online ISBN: 978-3-319-10554-3
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