Peak signal-to-noise ratio based on threshold method for image segmentation

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Binarization or thresholding is one problem that must be solved in pattern recognition and it has a very important influence on the sequent steps in imaging applications. Thresholding is used to separate objects from the background, and diminish the amount of data alter the computational speed. Recently, interest in multilevel thresholding has been altered. However, when the levels are altered, the computation time alters so single threshold methods are accelerated than multilevel methods. Moreover, for every new application, new methods are is acquired. In this work, a new algorithm which used the gain signal-to-noise ratio method as an indicator to segment the image is aimed. The algorithm which is used the DIBCO 2011 in printed and a handwritten image was tested. This method has a better performance than new methods, such as Kittler and Illingworth's Minimum Error Thresholding, potential difference and Otsu.

Original languageEnglish
Pages (from-to)158-168
Number of pages11
JournalJournal of Theoretical and Applied Information Technology
Volume57
Issue number2
Publication statusPublished - 2013

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Image segmentation
Image Segmentation
Signal to noise ratio
Thresholding
Pattern recognition
Imaging techniques
Binarization
Multilevel Methods
Pattern Recognition
Imaging

Keywords

  • Image processing
  • Image segmentation
  • Optical character recognition
  • PSNR
  • Single thresholding

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

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abstract = "Binarization or thresholding is one problem that must be solved in pattern recognition and it has a very important influence on the sequent steps in imaging applications. Thresholding is used to separate objects from the background, and diminish the amount of data alter the computational speed. Recently, interest in multilevel thresholding has been altered. However, when the levels are altered, the computation time alters so single threshold methods are accelerated than multilevel methods. Moreover, for every new application, new methods are is acquired. In this work, a new algorithm which used the gain signal-to-noise ratio method as an indicator to segment the image is aimed. The algorithm which is used the DIBCO 2011 in printed and a handwritten image was tested. This method has a better performance than new methods, such as Kittler and Illingworth's Minimum Error Thresholding, potential difference and Otsu.",
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