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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References
Wong, K.Y., Casey, R.G., Wahl, F.M.: Document analysis system. IBM J. Res. Dev. 26, 647–656 (1982)
Gatos, B., Mantzarisl, S., Antonacopoulos, A.: First international newspaper segmentation contest. In: Proceedings of the 6th International Conference on Document Analysis and Recognition, pp. 1190–1194 (2001)
Liu, F., Luo, Y., Yoshikawa, M., Hu, D.: A new component based algorithm for newspaper layout analysis. In: Proceedings of the 6th International Conference on Document Analysis and Recognition (ICDAR), pp. 1176–1179. IEEE Computer Society (2001)
Jain, A.K., Yu, B.: Document representation and its application to page decomposition. IEEE Trans. Pattern Anal. Mach. Intell. J. 20, 294–308 (1998)
Mitchell, P.E., Yan, H.: Newspaper document analysis featuring connected line segmentation. In: 6th International Conference on Document Analysis and Recognition, pp. 1181–1185 (2001)
Hadjar, K., Ingold, R.: Arabic newspaper page segmentation. In: 7th International Conference on Document Analysis and Recognition, pp. 895–899 (2003)
Antonacopoulos, C., Clausner, C., Papadopoulos, S., Pletschacher, S.: Historical document layout analysis competition. In: Proceedings of the 11th International Conference on Document Analysis and Recognition, pp. 1516–1520 (2011)
Antonacopoulos, A., Pletschacher, S., Bridson, D., Papadopoulos, C.: ICDAR 2009 page segmentation competition. In: 10th International Conference on Document Analysis and Recognition, University of Salford, pp. 1370–1374 (2009)
Robadey, L.: 2 (CREM): Une méthode de reconnaissance structurelle de documents complexes basée sur des patterns bidimensionnels, Doctoral thesis, University of Friborg-Suisse (2001)
Hadjar, K., Hitz, O., Ingold, R.: Newspaper page decomposition using a split and merge approach. In: 6th International Conference on Document Analysis and Recognition (ICDAR), pp. 1186–1189 (2001)
Palfray, T., Hébert, D., Tranouez, P., Nicolas, S., Paquet, T.: Segmentation logique d’images de journaux anciens, Francophone International Conference on Writing and Document, p. 317 (2012)
Boufersaoui, H., Frihi, I.: Extraction of the logical structure of documents, Master’s thesis of Media Engineering, University, 08 May 1945-Guelma (2015)
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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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