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Adaptive uneven illumination correction method of document images.

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Title: Adaptive uneven illumination correction method of document images.
Authors: Fanfeng Zeng1, Shupeng Liu1 13070195207@163.com, Ke Xiao1
Source: Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.). 2017, Vol. 17 Issue 3, p533-544. 12p.
Subjects: Document imaging systems, Adaptive codes, Optical character recognition, Problem solving, Binary number system, Lighting
Abstract: Under condition of uneven illumination, directly recognizing the document image by OCR would lead to a bad effect, which is a difficult point in document recognition. To solve this problem above, a Retinex-based illumination correction method was proposed. Firstly, the images were supposed to be divided into blocks, which were processed respectively by Otsu binarization. The light conditions can be got through the feedback results of processing, which helps to have uneven illumination image blocks achieved. Then images can be enhanced by the improved Retinex method, which extends dynamic range of image block gray value and enhances details of image block. Finally, images can be corrected by sauvola binarization processing. Experimental results show that the algorithm can eliminate the impact of uneven illumination. Compared with the common local binarization and enhancement methods, the OCR recognition rates are significantly increased. At the same time, the combination of global and local methods promotes the applicable scope of being in condition of samples and different illumination. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 124640471
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PubTypeId: academicJournal
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IllustrationInfo
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  Data: Adaptive uneven illumination correction method of document images.
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  Data: <searchLink fieldCode="AR" term="%22Fanfeng+Zeng%22">Fanfeng Zeng</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Shupeng+Liu%22">Shupeng Liu</searchLink><relatesTo>1</relatesTo><i> 13070195207@163.com</i><br /><searchLink fieldCode="AR" term="%22Ke+Xiao%22">Ke Xiao</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="DE" term="%22Document+imaging+systems%22">Document imaging systems</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+codes%22">Adaptive codes</searchLink><br /><searchLink fieldCode="DE" term="%22Optical+character+recognition%22">Optical character recognition</searchLink><br /><searchLink fieldCode="DE" term="%22Problem+solving%22">Problem solving</searchLink><br /><searchLink fieldCode="DE" term="%22Binary+number+system%22">Binary number system</searchLink><br /><searchLink fieldCode="DE" term="%22Lighting%22">Lighting</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Under condition of uneven illumination, directly recognizing the document image by OCR would lead to a bad effect, which is a difficult point in document recognition. To solve this problem above, a Retinex-based illumination correction method was proposed. Firstly, the images were supposed to be divided into blocks, which were processed respectively by Otsu binarization. The light conditions can be got through the feedback results of processing, which helps to have uneven illumination image blocks achieved. Then images can be enhanced by the improved Retinex method, which extends dynamic range of image block gray value and enhances details of image block. Finally, images can be corrected by sauvola binarization processing. Experimental results show that the algorithm can eliminate the impact of uneven illumination. Compared with the common local binarization and enhancement methods, the OCR recognition rates are significantly increased. At the same time, the combination of global and local methods promotes the applicable scope of being in condition of samples and different illumination. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.3233/JCM-170740
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 12
        StartPage: 533
    Subjects:
      – SubjectFull: Document imaging systems
        Type: general
      – SubjectFull: Adaptive codes
        Type: general
      – SubjectFull: Optical character recognition
        Type: general
      – SubjectFull: Problem solving
        Type: general
      – SubjectFull: Binary number system
        Type: general
      – SubjectFull: Lighting
        Type: general
    Titles:
      – TitleFull: Adaptive uneven illumination correction method of document images.
        Type: main
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          Name:
            NameFull: Fanfeng Zeng
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          Name:
            NameFull: Shupeng Liu
      – PersonEntity:
          Name:
            NameFull: Ke Xiao
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          Dates:
            – D: 01
              M: 07
              Text: 2017
              Type: published
              Y: 2017
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              Value: 17
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              Value: 3
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            – TitleFull: Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.)
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