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OCR System for Poor Quality Images Using Chain-Code Representation

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The 1st International Conference on Advanced Intelligent System and Informatics (AISI2015), November 28-30, 2015, Beni Suef, Egypt

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 407))

Abstract

The field of Optical Character Recognition (OCR) has gained more attention in the recent years because of its importance and applications. Some examples of OCR are: video indexing, references archiving, car-plate recognition, and data entry. In this work a robust system for OCR is presented. The proposed system recognizes text in poor quality images. Characters are extracted from the given poor quality image to be recognized using chain-code representation. The proposed system uses Google online spelling to suggest replacements for words which are misspelled during the recognition process. For evaluating the proposed system, the born-digital dataset ICDAR is used. The proposed system achieves 74.02 % correctly recognized word rate. The results demonstrate that the proposed system recognizes text in poor quality images efficiently.

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Notes

  1. 1.

    http://www.free-ocr.com/.

  2. 2.

    http://www.newocr.com/.

  3. 3.

    http://www.google.com.

  4. 4.

    http://www.onlineocr.net/.

  5. 5.

    https://play.google.com/store/apps/details?id=com.google.android.apps.translate.

  6. 6.

    http://finereader.abbyy.com/.

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Author information

Authors and Affiliations

  1. Assiut University, Asyut, Egypt

    Ali H. Ahmed, Mahmoud Afifi, Mostafa Korashy, Ebram K. William, Mahmoud Abd El-sattar & Zenab Hafez

Authors
  1. Ali H. Ahmed
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  2. Mahmoud Afifi
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  3. Mostafa Korashy
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  4. Ebram K. William
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  5. Mahmoud Abd El-sattar
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  6. Zenab Hafez
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Corresponding author

Correspondence to Mahmoud Afifi .

Editor information

Editors and Affiliations

  1. Faculty of Computers & Informatics, Suez Canal University, Ismailia, Egypt

    Tarek Gaber

  2. Department of Information Technology, Cairo University Faculty of Computers & Information, Giza, Egypt

    Aboul Ella Hassanien

  3. College of Management and Technology, Arab Academy for Science, Technology, and Maritime Transport, Giza, Egypt

    Nashwa El-Bendary

  4. Bengal College of Engineering and Technology, Durgapur, West Bengal, India

    Nilanjan Dey

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Ahmed, A.H., Afifi, M., Korashy, M., William, E.K., El-sattar, M.A., Hafez, Z. (2016). OCR System for Poor Quality Images Using Chain-Code Representation. In: Gaber, T., Hassanien, A., El-Bendary, N., Dey, N. (eds) The 1st International Conference on Advanced Intelligent System and Informatics (AISI2015), November 28-30, 2015, Beni Suef, Egypt. Advances in Intelligent Systems and Computing, vol 407. Springer, Cham. https://doi.org/10.1007/978-3-319-26690-9_14

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  • DOI: https://doi.org/10.1007/978-3-319-26690-9_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26688-6

  • Online ISBN: 978-3-319-26690-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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