Skip to main content

Partial Differential Equation (PDE) Based Image Smoothing System for Digital Radiographic Image

  • Conference paper
  • First Online:
Soft Computing in Data Science (SCDS 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 545))

Included in the following conference series:

  • 1182 Accesses

Abstract

Over the last few decades, partial differential equations (PDEs) have become one of the significant mathematical methods that are widely used in the current image processing area. One of its common applications is in image smoothing which is an essential preliminary step in image processing. Smoothing is necessary because it affects the result of further processes in image processing. In this project, a system based on second-order PDE and fourth-order PDE models are developed and implemented in digital radiographic image that contain welding defects. The results obtained from these models show better image quality as compared to conventional filters, such as median filter and Gaussian filter. The system is beneficial in assisting radiographic inspectors to produce a better evaluation and analysis on defects in welding images. In addition, non-destructive testing consultants from industries and academician from universities can also utilize this system for training and research purposes.

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

Access this chapter

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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Berthel, A., Bonin, T., Cadilhon, S., Chatellier, L., Kaftandjian, V., Honorat, P., et al.: Digital Radiography: Description and User’s Guide. In: International Symposium on Digital industrial Radiology and Computed Tomography, Lyon, France (2007)

    Google Scholar 

  2. Noorhazleena.: Computed radiography (CR) Signal to Noise Ratio (SNR) Study based on Thickness Changes of Steel Step Wedge. Malaysian Society for Non-Destructive Testing, MSNT (2010)

    Google Scholar 

  3. Leavline, E.J., Singh, D.A.A.G.: On Teaching Digital Image Processing with MATLAB. American Journal of Signal Processing 2014 4, 7–15 (2014)

    Google Scholar 

  4. Gonzales, R.C., Woods, R.E.: Digital Image Processing. Prentice Hall, New Jersey (2002)

    Google Scholar 

  5. Ery, A.C., David, L.D.: Does Median Filtering Truly Preserve Edges Better Than Linear Filtering? The Annals of Statistics 37, 1172–1206 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  6. Chhabra, T., Dua, G., Malhotra, T.: Comparative Analysis of Denoising Methods in CT Images. International Journal of Emerging Trends in Electrical and Electronics 3, 56–59 (2013)

    Google Scholar 

  7. Wang, H., Wang, Y., Ren, W.: Image Denoising using Anisotropic Second and Fourth Order Diffusions Based on Gradient Vector Convolution. Journal on ComSIS 9, 1493–1511 (2012)

    Article  Google Scholar 

  8. Jing, J., Kehu, Y., Jianjun, G., Wensheng, Y.: Journal of Institute of Electrical and Electronics Engineers, 332–334 (2007)

    Google Scholar 

  9. Liu, T., Xiang, Z.: Journal on Mathematical Problems in Engineering 2013, 1–7 (2013)

    Google Scholar 

  10. Perona, P., Malik, J.: Scale-Space and Edge Detection using Anisotropic Diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence 12, 629–639 (1990)

    Article  Google Scholar 

  11. Wee, L.K., Chai, H.Y., Supriyanto, E.: Computerized Anisotropic Diffusion of Two Dimensional Ultrasonic Images using Multi-Direction Spreading Approaches. WSEAS Transactions on Biology and Biomedicine 3, 102–112 (2011)

    Google Scholar 

  12. Shanmugam, K., RSD, W.: Condensed Anisotropic Diffusion for Speckle Reduction and Enhancement in Ultrasonography. EURASIP Journal on Image and Video Processing 2012, 1–17 (2012)

    Google Scholar 

  13. You, Y.L., Kaveh, M.: Fourth-Order Partial Differential Equations for Noise Removal. IEEE Transactions on Image Processing 9, 1723–1730 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  14. Hajiaboli, M.R.: An Anisotropic Fourth-Order Partial Differential Equation for Noise Removal. In: Tai, X.-C., Mørken, K., Lysaker, M., Lie, K.-A. (eds.) SSVM 2009, vol. 5567, pp. 356–367. Springer, Heidelberg (2009)

    Google Scholar 

  15. Kumar, A., Kaushik, A.K., Anuradha, S.D.: A New Hybrid Model to Detect the Mammogram Images for Early Breast Cancer. International Journal on Emerging Technologies 1, 28–31 (2010)

    Google Scholar 

  16. Hartson, H.R.: Human Computer Interaction: Interdisciplinary Roots and Trends. The Journal of Systems and Software 43, 103–118 (1998)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Suhaila Abd Halim .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Science+Business Media Singapore

About this paper

Cite this paper

Halim, S.A., Ibrahim, A., Manurung, Y.H. (2015). Partial Differential Equation (PDE) Based Image Smoothing System for Digital Radiographic Image. In: Berry, M., Mohamed, A., Yap, B. (eds) Soft Computing in Data Science. SCDS 2015. Communications in Computer and Information Science, vol 545. Springer, Singapore. https://doi.org/10.1007/978-981-287-936-3_19

Download citation

  • DOI: https://doi.org/10.1007/978-981-287-936-3_19

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-287-935-6

  • Online ISBN: 978-981-287-936-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics