Abstract
In document analysis and recognition, we seek to apply methods of automatic document identification. The main goal is to go from a simple image to a structured set of information exploitable by machine. Here, we present a system for recognizing the logical structure (hierarchical organization) of Arabic newspapers pages. These are characterized by a rich and variable structure. They may contain several articles composed of titles, figures, author’s names and figure captions. However, the logical structure recognition of a newspaper page is preceded by the extraction of its physical structure. This extraction is performed in our system using a combined method which is essentially based on the RLSA (Run Length Smearing/Smoothing Algorithm) [1], projections profile analysis, and connected components labeling. Logical structure extraction is then performed based on certain rules of sizes and positions of the physical elements extracted earlier, and also on an a priori knowledge of certain properties of logical entities (titles, figures, authors, captions, etc.). Lastly, the hierarchical organization of the document is represented as an XML file generated automatically. To evaluate the performance of our system, we tested it on a set of images and the results are encouraging.
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Bouressace, H., Csirik, J. (2018). Recognition of the Logical Structure of Arabic Newspaper Pages. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech, and Dialogue. TSD 2018. Lecture Notes in Computer Science(), vol 11107. Springer, Cham. https://doi.org/10.1007/978-3-030-00794-2_27
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DOI: https://doi.org/10.1007/978-3-030-00794-2_27
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