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A Novel Baseline Detection Method of Handwritten Arabic-Script Documents Based on Sub-Words

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Soft Computing Applications and Intelligent Systems (M-CAIT 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 378))

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Abstract

Baseline detection is an important process in document image analysis and recognition systems. It is extensively used to many various preprocessing stages such as text normalization, skew correction, characters segmentation, slant and slop correction as well as in feature extraction. in this work, we proposed a new method for baseline detection based on horizontal projection histogram and directions features of subwords skeleton for Arabic script; which form the main component of the text that may consist of at least one letter, in addition of diacritic and dots. The efficiency of the proposed method is has been proven by the experiment’s results on an IFN/ENIT Arabic benchmark dataset.

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References

  1. U. Nations, http://www.un.org (March 13, 2013)

  2. Abu-Ain, T.A.H., Abu-Ain, W.A.H., Sheikh Abdullah, S.N.H., Omar, K.: Off-line Arabic Character-Based Writer Identification – a Survey. In: International Journal on Advanced Science, Engineering and Information Technology, pp. 161–166 (2011); Proceeding of the International Conference on Advanced Science, Engineering and Information Technology Bangi, Malaysia

    Google Scholar 

  3. Bataineh, B., Abdullah, S.N.H.S., Omar, K.: Arabic calligraphy recognition based on binarization methods and degraded images. In: International Conference in Pattern Analysis and Intelligent Robotics (ICPAIR 2011), pp. 65–70 (2011)

    Google Scholar 

  4. Gacek, A.: Arabic Manuscripts: A Vademecum for Readers, BRILL (2009)

    Google Scholar 

  5. Parhami, B., Taraghi, M.: Automatic Recognition of Printed Farsi Texts. Presented at the Proc. Conf. Pattern Recognition, England (1980)

    Google Scholar 

  6. Pechwitz, M., Margner, V.: Baseline estimation for Arabic handwritten words. In: Proceeding in Eighth International Workshop on Frontiers and Handwriting Recognition, pp. 479–484 (2002)

    Google Scholar 

  7. Farooq, F., Govindaraju, V., Perrone, M.: Pre-processing methods for handwritten Arabic documents. In: Proceedings in Eighth International Conference on Document Analysis and Recognition, vol. 1, pp. 267–271 (2005)

    Google Scholar 

  8. Ziaratban, M., Faez, K.: A novel two-stage algorithm for baseline estimation and correction in Farsi and Arabic handwritten text line. In: 19th International Conference on Pattern Recognition, ICPR 2008, pp. 1–5 (2008)

    Google Scholar 

  9. Boubaker, H., Kherallah, M., Alimi, A.M.: New Algorithm of Straight or Curved Baseline Detection for Short Arabic Handwritten Writing. In: 10th International Conference on Document Analysis and Recognition, ICDAR 2009, pp. 778–782 (2009)

    Google Scholar 

  10. Boukerma, H., Farah, N.: A Novel Arabic Baseline Estimation Algorithm Based on Sub-Words Treatment. In: International Conference on Frontiers in Handwriting Recognition (ICFHR 2010), pp. 335–338 (2010)

    Google Scholar 

  11. Nagabhushan, P., Alaei, A.: Tracing and Straightening the Baseline in Handwritten Persian/Arabic Text-line: A New Approach Based on Painting-technique. International Journal on Computer Science and Engineering 2, 907–916 (2010)

    Google Scholar 

  12. Bataineh, B., Abdullah, S.N.H.S., Omar, K.: An adaptive local binarization method for document images based on a novel thresholding method and dynamic windows. Pattern Recognition Letters 32, 1805–1813 (2011)

    Article  Google Scholar 

  13. Linda, G.C.S., Shapiro, G.: Computer Vision. Prentice Hall (2002)

    Google Scholar 

  14. Abu-Ain, W., Abdullah, S.N.H.S., Bataineh, B., Abu-Ain, T., Omar, K.: Skeletonization Algorithm for Binary Images. In: International Conference on Electrical Engineering and Informatics, ICEEI 2013 (2013)

    Google Scholar 

  15. IFN/ENIT - Database of Arabic Handwritten words, T. U. Institute of Communications Technology, Braunschweig, Germany (2002)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Pattern Recognition Research Group, Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Tarik Abu-Ain, Siti Norul Huda Sheikh Abdullah, Bilal Bataineh & Khairuddin Omar

  2. Computer Engineering Department, Al-Balqa’ Applied University, Faculty of Engineering Technology, Amman, Jordan

    Ashraf Abu-Ein

Authors
  1. Tarik Abu-Ain
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  2. Siti Norul Huda Sheikh Abdullah
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  3. Bilal Bataineh
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  4. Khairuddin Omar
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  5. Ashraf Abu-Ein
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Editor information

Editors and Affiliations

  1. Faculty of Information Science & Technology, University Kebangsaan Malaysia, Bangi, Selangor, Malaysia

    Shahrul Azman Noah

  2. Center for Artificial Intelligence Technology (CAIT), Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor D. E, Malaysia

    Azizi Abdullah

  3. Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor Darul Ehsan, Malaysia

    Haslina Arshad , Zulaiha Ali Othman  & Zalinda Othman ,  & 

  4. School of Computer Science, FTSM, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor Darul Ehsan, Malaysia

    Azuraliza Abu Bakar

  5. Pattern Recognition Research Group, CAIT, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Shahnorbanun Sahran

  6. Faculty of Information Science & IT, National University of Malaysia, 43600, Bangi, Selangor, Malaysia

    Nazlia Omar

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Abu-Ain, T., Sheikh Abdullah, S.N.H., Bataineh, B., Omar, K., Abu-Ein, A. (2013). A Novel Baseline Detection Method of Handwritten Arabic-Script Documents Based on Sub-Words. In: Noah, S.A., et al. Soft Computing Applications and Intelligent Systems. M-CAIT 2013. Communications in Computer and Information Science, vol 378. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40567-9_6

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  • DOI: https://doi.org/10.1007/978-3-642-40567-9_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40566-2

  • Online ISBN: 978-3-642-40567-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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