Abstract
The paper proposes a new method for characterization and distinction between closely related languages on the example of Serbian and Croatian languages. In the first step, the method transforms the text in different languages into the uniformly coded text. It is carried out in accordance to the position of each sign of the script in the text line and its height. Then, the coded text given as 1-D image is subjected to the texture analysis. According to that analysis, a feature vector of 28 elements is established. These 28 elements are extracted from co-occurrence texture and adjacent local binary pattern analysis. The feature vector is a starting point for classification by an extension of a state of the art method, called GA-ICDA. As a result, the distinction between the closely related languages is correctly accomplished. The method is tested on a database of documents in Serbian and Croatian languages. The experiments give promising results.
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Brodić, D., Amelio, A., Milivojević, Z.N. (2015). Characterization and Distinction Between Closely Related South Slavic Languages on the Example of Serbian and Croatian. In: Azzopardi, G., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2015. Lecture Notes in Computer Science(), vol 9256. Springer, Cham. https://doi.org/10.1007/978-3-319-23192-1_55
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DOI: https://doi.org/10.1007/978-3-319-23192-1_55
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