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Computational Intelligence in Data Mining - Volume 2 pp 99–110Cite as

Design of Biorthogonal Wavelets Based on Parameterized Filter for the Analysis of X-ray Images

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 32))

Abstract

The X-ray bone images are extensively used by the medical practitioners to detect the minute fractures as they are painless and economical compared to other image modalities. This paper proposes a parameterized design of biorthogonal wavelet based on the algebraical construction method. In order to assign the characters of biorthogonal wavelet, there are two kinds of parameters which are introduced in construction process. One is scale factor and another one is sign factor. In edge detection, the necessary condition of wavelet design is put forward and two wavelet filers are built. The simulation results show that the parameterized design of biorthogonal wavelet is simple and feasible. The biorthogonal wavelet zbo6.6 performs well in detecting the edges with better quality. The various performance metrics like Ratio of Edge pixels to size of image (REPS), peak signal to noise ratio (PSNR) and computation time are compared for various biorthogonal wavelets.

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References

  1. Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Pearson Education, Upper Saddle River (2004)

    Google Scholar 

  2. Cui, F.Y., Zou L.J., Song B.: Edge feature extraction based on digital image processing techniques. In: Proceedings of the IEEE International Conference on Automation and Logistics, pp. 2320–2324, Qingdao, China (2008)

    Google Scholar 

  3. Verma, R., Mahrishi, R., Srivastava, G.K., Siddavatam, R.: A novel image reconstruction using second generation wavelets. In: International Conference on Advances in Recent Technologies in Communication and Computing (2009). doi:10.1109/ARTCom.2009.59. ISBN 978-0-7695-3845-7

  4. Soman, B.K.P., Ramachandran, B.K.P.: Insight into Wavelets from Theory to Practice, 2nd edn. PHI, New Delhi (2008)

    Google Scholar 

  5. Vanfleet, P.J.: Discrete Wavelet Transformations an Elementary Approach with Applications. Wiley, Hoboken

    Google Scholar 

  6. Han, D.B., Ron, A., Shen, Z.B.: Framelets: MRA based constructions of wavelet frames. Appl. Comput. Harmonic Anal. 14, 146 (2003)

    MathSciNet  Google Scholar 

  7. Changzhen, X.: Construction of biorthogonal two-direction refinable function and two-direction wavelet with dilation factor m. Comput. Math. Appl. 56(7), 1845–1851 (2008)

    Google Scholar 

  8. Rosca, D., Antoine, J.P.: Locally supported orthogonal wavelet bases on the sphere via stereographic projection. Math. Probl. Eng. Article ID 124904 (2009)

    Google Scholar 

  9. Rafieea, J.: A novel technique for selecting mother wavelet function using an intelligent fault diagnosis system. Expert Syst. Appl. 36(3), 4862–4875 (2009)

    Google Scholar 

  10. Khera, S., Malhotra S.: Survey on medical image de noising using various filters and wavelet transform. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 4(4), 230–234 (2014)

    Google Scholar 

  11. Benedetto, J.J., Li, S.: The theory of multi resolution analysis frames and applications to filter banks. Appl. Comput. Harmonic Anal. 5(4), 389–427 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  12. Chaudhury, K.N.: Construction of Hilbert transform pairs of wavelet bases and Gabor-like transforms. Signal Proc. 57(9), 3411–3425 (2009)

    Article  MathSciNet  Google Scholar 

  13. Qiang, Z., Xiaodong, C., Hongxi, W., Ping, L.: Parametrized algebraical construction method of biorthogonal wavelet. In: 3rd International Conference on Computer Science and Information Technology (ICCSIT 2010)

    Google Scholar 

  14. Vidya, P., Veni, S., Narayanankutty, K.A.: Performance analysis of edge detection methods on hexagonal sampling grid. Int. J. Electron. Eng. Res. 1(4), 313–328 (2009). ISSN 0975–6450

    Google Scholar 

  15. Kudale G.A., Pawar M.D.: Study and analysis of various edge detection methods for X-ray images. Int. J. Comput. Sci. Appl. (2010)

    Google Scholar 

  16. Lizhen, L.: Discussion of digital image edge detection method. Mapp. Aviso 3, 40–42 (2006)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of ECE, GMR Institute of Technology, Rajam, India

    P. M. K. Prasad

  2. Department of ECE, AITAM, Tekkali, India

    M. N. V. S. S. Kumar

  3. Department of ECE, Andhra University College of Engineering, Visakhapatnam, India

    G. Sasi Bhushana Rao

Authors
  1. P. M. K. Prasad
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  2. M. N. V. S. S. Kumar
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  3. G. Sasi Bhushana Rao
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Corresponding author

Correspondence to P. M. K. Prasad .

Editor information

Editors and Affiliations

  1. University of Canberra, Canberra, Australia and University of South Australia, Adelaide, South Australia, Australia

    Lakhmi C. Jain

  2. Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  3. Computer Science & Engineering, Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  4. Dept. of Computer Science and Engineering, National Institute of Technology Rourkela, Rourkela, India

    Durga Prasad Mohapatra

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Prasad, P.M.K., Kumar, M.N.V.S.S., Sasi Bhushana Rao, G. (2015). Design of Biorthogonal Wavelets Based on Parameterized Filter for the Analysis of X-ray Images. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 2. Smart Innovation, Systems and Technologies, vol 32. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2208-8_11

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  • DOI: https://doi.org/10.1007/978-81-322-2208-8_11

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2207-1

  • Online ISBN: 978-81-322-2208-8

  • eBook Packages: EngineeringEngineering (R0)

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