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Improvement of binarization performance using local otsu thresholding

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 9 No. 1 (2019)

DOI
10.11591/ijece.v9i1.pp264-272
ISSN
2088-8708, 2088-8708
Published
2019-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Ancient document usually contains multiple noises such as uneven-background, show-through, water-spilling, spots, and blur text. The noise will affect the binarization process. Binarization is an extremely important process in image processing, especially for character recognition. This paper presents an improvement to Nina binarization technique. Improvements were achieved by reducing processing steps and replacing median filtering by Wiener filtering. First, the document background was approximated by using Wiener filter, and then image subtraction was applied. Furthermore, the manuscript contrast was adjusted by mapping intensity of image value using intensity transformation method. Next, the local Otsu thresholding was applied. For removing spotting noise, we applied labeled connected component. The proposed method had been testing on H-DIBCO 2014 and degraded Jawi handwritten ancient documents. It performed better regarding recall and precision values, as compared to Otsu, Niblack, Sauvola, Lu, Su, and Nina, especially in the documents with show-through, water-spilling and combination noises.

Collaboration network of the authors

20 authors · 38 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Syiah Kuala
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Nasaruddin NasaruddinUniversitas Syiah Kuala2
Yunida YunidaUniversitas Syiah Kuala2
Fachrurrazi FachrurraziUniversitas Syiah Kuala2
Hendra HidayatUniversitas Syiah Kuala2
Roslidar RoslidarUniversitas Syiah Kuala2
Ramadhani RamadhaniUniversitas Syiah Kuala1
Rusdha MuhararUniversitas Syiah Kuala1
Kahlil MuchtarUniversitas Syiah Kuala1
Nyak Twoman AnshariUniversitas Syiah Kuala1
Chairuman ChairumanUniversitas Syiah Kuala1
Khalid AlhabibieUniversitas Syiah Kuala1
Saiful HusinUniversitas Syiah Kuala1
Zulfikar ZulfikarUniversitas Syiah Kuala1
Rafiqa Shahnaz NoorUniversitas Syiah Kuala1
Abdullah AbdullahUniversitas Syiah Kuala1
Teuku Budi AuliaUniversitas Syiah Kuala1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Improvement of binarization performance using local otsu thresholding</dc:title><dc:creator>Saddami, Khairun</dc:creator><dc:creator>Munadi, Khairul</dc:creator><dc:creator>Away, Yuwaldi</dc:creator><dc:creator>Arnia, Fitri</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;Ancient document usually contains multiple noises such as uneven-background, show-through, water-spilling, spots, and blur text. The noise will affect the binarization process. Binarization is an extremely important process in image processing, especially for character recognition. This paper presents an improvement to Nina binarization technique. Improvements were achieved by reducing processing steps and replacing median filtering by Wiener filtering. First, the document background was approximated by using Wiener filter, and then image subtraction was applied. Furthermore, the manuscript contrast was adjusted by mapping intensity of image value using intensity transformation method. Next, the local Otsu thresholding was applied. For removing spotting noise, we applied labeled connected component. The proposed method had been testing on H-DIBCO 2014 and degraded Jawi handwritten ancient documents. It performed better regarding recall and precision values, as compared to Otsu, Niblack, Sauvola, Lu, Su, and Nina, especially in the documents with show-through, water-spilling and combination noises.&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2019-02-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v9i1.pp264-272</dc:identifier><dc:identifier>10.11591/ijece.v9i1.pp264-272</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 9 No 1 (2019); 264</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/11742/12031</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>