Adaptive thresholding methods for documents image binarization

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Binarization process is easy when applying simple thresholding method onto good quality image. However, this task becomes difficult when it deals with degraded image. Most current binarization methods involve complex algorithm and less ability to recover important information from a degradation image. We introduce an adaptive binarization method to overcome the state of the art. This method also aims to solve the problem of the low contrast images and thin pen stroke problems. It can also enhance the effectiveness of solving all other problems. As well as, it does not need to specify the values of the factors manually. We compare the proposed method with known thresholding methods, which are Niblack, Sauvola, and NICK methods. The results show that the proposed method gave higher performance than previous methods.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages230-239
Number of pages10
Volume6718 LNCS
DOIs
Publication statusPublished - 2011
Event3rd Mexican Conference on Pattern Recognition, MCPR 2011 - Cancun
Duration: 29 Jun 20112 Jul 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6718 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other3rd Mexican Conference on Pattern Recognition, MCPR 2011
CityCancun
Period29/6/112/7/11

Fingerprint

Adaptive Thresholding
Binarization
Image quality
Degradation
Thresholding
Stroke
Image Quality
High Performance

Keywords

  • binarization
  • document image
  • local binarization
  • thresholding method

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Bataineh, B., Sheikh Abdullah, S. N. H., Omar, K., & Nasrudin, M. F. (2011). Adaptive thresholding methods for documents image binarization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6718 LNCS, pp. 230-239). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6718 LNCS). https://doi.org/10.1007/978-3-642-21587-2_25

Adaptive thresholding methods for documents image binarization. / Bataineh, Bilal; Sheikh Abdullah, Siti Norul Huda; Omar, Khairuddin; Nasrudin, Mohammad Faidzul.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6718 LNCS 2011. p. 230-239 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6718 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Bataineh, B, Sheikh Abdullah, SNH, Omar, K & Nasrudin, MF 2011, Adaptive thresholding methods for documents image binarization. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 6718 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6718 LNCS, pp. 230-239, 3rd Mexican Conference on Pattern Recognition, MCPR 2011, Cancun, 29/6/11. https://doi.org/10.1007/978-3-642-21587-2_25
Bataineh B, Sheikh Abdullah SNH, Omar K, Nasrudin MF. Adaptive thresholding methods for documents image binarization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6718 LNCS. 2011. p. 230-239. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-21587-2_25
Bataineh, Bilal ; Sheikh Abdullah, Siti Norul Huda ; Omar, Khairuddin ; Nasrudin, Mohammad Faidzul. / Adaptive thresholding methods for documents image binarization. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6718 LNCS 2011. pp. 230-239 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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