Skip to main content

Medical Image Binarization Using Square Wave Representation

  • Conference paper

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 140))

Abstract

This paper describes a new approach for medical image binarization based on square wave representation. A square wave is a type of wave form, where the input signal has two levels +1 (foreground) and -1 (background). The signal switches between these levels based on the threshold value computed at that level with the specified time interval. In this method, a local threshold value is calculated at every interval using the current intensity value. Then, the image pixel is assigned with a value +1 or -1 using this local threshold value. The experimental results show that the proposed method reduces the complexity and increases the seperability factor in medical image segmentation. The result obtained by our method is comparable to or better than Otsu’s thresholding method.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Pal, N.R., Pal, S.K.: A Review on Image Segmentation Techniques. Pattern Recognition 26, 1277–1294 (1993)

    Article  Google Scholar 

  2. Sahoo, P.K., Soltani, S., Wong, A.K.C.: A Survey of Thresholding Techniques. Computer Vision Graphics and Image Processing 41, 233–260 (1988)

    Article  Google Scholar 

  3. Trier, O.D., Jain, A.K.: Goal-Directed Evaluation of Binarization Methods. IEEE Transaction on Pattern. Analysis and Machine Intelligence 17, 1191–1201 (1995)

    Article  Google Scholar 

  4. Trier, O.D., Taxt, T.: Evaluation of Binarization Methods for Document Images. IEEE Transaction on Pattern. Analysis and Machine Intelligence 17, 312–315 (1995)

    Article  Google Scholar 

  5. Sezgin, M., Sankur, B.: Survey over Image Thresholding Techniques and Quantitative Performance Evaluation. Journal of Electronic Imaging 13(1), 146–165 (2004)

    Article  Google Scholar 

  6. Lee, S.U., Chung, S.Y., Park, R.H.: A Comparative Performance Study of Several Global Thresholding Techniques for Segmentation. Computer Vision, Graphics and Image Processing 52, 171–190 (1990)

    Article  Google Scholar 

  7. Otsu, N.: A Threshold Selection Method from Gray-level Histograms. IEEE Transaction on Systems, Man, and Cybernetics 9(1), 62–66 (1979)

    Article  MathSciNet  Google Scholar 

  8. Maths Reference available online, http://www.mathreference.com

  9. IBSR data set available online, http://www.cma.mgh.harvard.edu/ibsr/index.html

  10. WBA (Whole Brain Atlas) MRI brain images available online, http://www.med.harvard.edu/AANLIB/home.html

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Somasundaram, K., Kalavathi, P. (2011). Medical Image Binarization Using Square Wave Representation. In: Balasubramaniam, P. (eds) Control, Computation and Information Systems. ICLICC 2011. Communications in Computer and Information Science, vol 140. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19263-0_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-19263-0_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19262-3

  • Online ISBN: 978-3-642-19263-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics