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Automatic Text Extraction from Arabic Newspapers

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Image Analysis and Recognition (ICIAR 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10882))

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Abstract

A system for extracting the textual information from document images with complex layouts is presented. It is based on both layout analysis and text localization techniques. Layout analysis is first applied to segment the page in text and non-text blocks and then text localization is used to detect text that may be embedded inside images, charts, diagrams, tables etc. Detailed experiments on scanned Arabic newspapers showed that combining layout analysis and text localization methods can lead to improved page segmentation and text extraction results.

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Author information

Authors and Affiliations

  1. University of the Aegean, Karlovasi, 83200, Samos, Greece

    Nikos Vasilopoulos & Ergina Kavallieratou

  2. Media Observer, Caracas Complex, Yajouz St 8, Amman, Jordan

    Yazan Wasfi

Authors
  1. Nikos Vasilopoulos
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  2. Yazan Wasfi
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  3. Ergina Kavallieratou
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Corresponding author

Correspondence to Nikos Vasilopoulos .

Editor information

Editors and Affiliations

  1. University of Porto, Porto, Portugal

    Aurélio Campilho

  2. University of Waterloo, Waterloo, Ontario, Canada

    Fakhri Karray

  3. Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands

    Bart ter Haar Romeny

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Vasilopoulos, N., Wasfi, Y., Kavallieratou, E. (2018). Automatic Text Extraction from Arabic Newspapers. In: Campilho, A., Karray, F., ter Haar Romeny, B. (eds) Image Analysis and Recognition. ICIAR 2018. Lecture Notes in Computer Science(), vol 10882. Springer, Cham. https://doi.org/10.1007/978-3-319-93000-8_57

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  • DOI: https://doi.org/10.1007/978-3-319-93000-8_57

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92999-6

  • Online ISBN: 978-3-319-93000-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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