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CRFs and HCRFs Based Recognition for Off-Line Arabic Handwriting

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Advances in Visual Computing (ISVC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9475))

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Abstract

This paper investigates the application of the probabilistic discriminative based Conditional Random Fields (CRFs) and its extension the hidden-states CRFs (HCRFs) to the problem of off-line Arabic handwriting recognition. A CRFs- and A HCRFs- based classifiers are built on top of an explicit word segmentation module using two different set of shape description features. A simple yet effective taxonomization technique is used to reduce the number of the class labels, and 3000 letter samples from IESK-arDB database are used for the training and 300 words are used for the evaluation. Experiments compare the performance of the CRFs to the HCRFs as well as to that of a generative based HMMs. Results indicate superiority of discriminative based approaches, where HCRFs achieved the best performance followed by CRFs.

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Acknowledgment

This work is supported by the National Plan for Science, Technology and Innovation (MAARIFAH) - King Abdulaziz City for Science and Technology(KACST) - KSA. Project code: 13-INF604-10.

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Authors and Affiliations

  1. Institute for Information Technology and Communications (IIKT), Otto-von-Guericke-University Magdeburg, P.O. Box 4210, 39016, Magdeburg, Germany

    Moftah Elzobi, Ayoub Al-Hamadi & Laslo Dings

  2. Umm Al-Qura University, Makkah, 21421, Saudi Arabia

    Sherif El-etriby

Authors
  1. Moftah Elzobi
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  2. Ayoub Al-Hamadi
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  3. Laslo Dings
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  4. Sherif El-etriby
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Corresponding author

Correspondence to Moftah Elzobi .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, Nevada, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, California, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, Nevada, USA

    Darko Koracin

  5. University of Houston, Houston, Texas, USA

    Ioannis Pavlidis

  6. IBM T.J. Watson Research Center, Yorktown Heights, New York, USA

    Rogerio Feris

  7. Purdue University, West Lafayette, Indiana, USA

    Tim McGraw

  8. Side Effects Software, Santa Monica, California, USA

    Mark Elendt

  9. The DiVE, Durham, North Carolina, USA

    Regis Kopper

  10. Texas A&M University, College Station, Texas, USA

    Eric Ragan

  11. Kent State University, Kent, Ohio, USA

    Zhao Ye

  12. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Gunther Weber

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Elzobi, M., Al-Hamadi, A., Dings, L., El-etriby, S. (2015). CRFs and HCRFs Based Recognition for Off-Line Arabic Handwriting. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9475. Springer, Cham. https://doi.org/10.1007/978-3-319-27863-6_31

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  • DOI: https://doi.org/10.1007/978-3-319-27863-6_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27862-9

  • Online ISBN: 978-3-319-27863-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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