Skip to main content
SpringerLink
Log in

Denoising Iris Image Using a Novel Wavelet Based Threshold

  • Conference paper
  • First Online:
Book cover Digital Connectivity – Social Impact (CSI 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 679))

Included in the following conference series:

Abstract

The efficiency of an iris authentication system depends on the quality of the iris image. Denoising of the iris image is indispensable to get a noise free image. In this paper, a novel method is proposed to remove Gaussian noise present in the iris image using Undecimated wavelet, a threshold based on Golden Ratio and weighted median. First, decompose the input image using Stationary Wavelet Transform (SWT) and apply the modified Visushrink to the wavelet coefficients using hard and soft thresholding. Then apply inverse SWT to get the noise free image. Different kinds of wavelet filters such as db1, db2, sym2, sym4, coif2 and coif4 for different noise levels are performed. The filter db1 is outperformed. In this research, experiments have been conducted on the iris database CASIA. The Peak Signal-to-Noise Ratio (PSNR), Signal-to-Noise Ratio (SNR), Root Mean Square Error (RMSE) and Mean Square Error (MSE) have been computed and compared.

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

Access this chapter

Log in via an institution

Institutional subscriptions

References

  1. Sutcu, Y., Tabassi, E., Sencar, H.T., Memon, N.: What is biometric information and how to measure it?. In: IEEE International Conference on Technologies for Homeland Security (HST), pp. 12–14 (2013)

    Google Scholar 

  2. Sasirekha, K., Thangavel, K.: A comparative analysis on fingerprint binarization techniques. Int. J. Comput. Intell. Inform. 4(3), 163–168 (2014)

    Google Scholar 

  3. Sasirekha, K., Thangavel, K.: A novel feature extraction algorithm from fingerprint ımage in wavelet domain. In. Senthilkumar, M., Ramasamy, V., Sheen, S., Veeramani, C., Bonato, A., Batten, L. (eds.) Intelligence, Cyber Security and Computational Models, ICC3 2015, Advances in Intelligent Systems and Computing, vol. 412, pp. 135–143. Springer, Heidelberg (2016)

    Google Scholar 

  4. Sanjay, N., Shrivastava, T.A., Upadhyay, A.R.: Advanced denoising technique for Iris images. In: International Conference on Systemics, Cybernetics and Informatics, vol. 3, pp. 106–109 (2011)

    Google Scholar 

  5. Sasirekha, K., Thangavel, K.: A novel wavelet based thresholding for denoising fingerprint ımage. In: IEEE International Conference on Electronics, Communication and Computational Engineering, pp. 119–124 (2014)

    Google Scholar 

  6. Mohideen, S.K., Perumal, S.A., Krishnan, N., Sathik, M.M., Kumar, T.C.R.: Image denoising multi-wavelet and threshold. In: IEEE International Conference on Computing, Communication and Networking, pp. 1– 5 (2008)

    Google Scholar 

  7. Donoho, D.L., Johnstone, I.M.: Ideal spatial adaptation via wavelet shrinkage. Biometrika 81, 425–455 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  8. Donoho, David L., Johnstone, I.M.: Adapting to unknown smoothness via wavelet shrinkage. J. Am. Stat. Assoc. 90(432), 1200–1224 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  9. Grace Chang, S., Yu, B., Vetterli, M.: Adaptive wavelet thresholding for ımage denoising and compression. IEEE Int. Trans. Image Process. 9(9), 1532–1546 (2000)

    Article  MATH  Google Scholar 

  10. Wavelet_Denoising. www.mors.org/UserFiles/file/…/Wavelet_Denoising.pdf

  11. Stakhov, A.P.: The generalized principle of the golden section and its applications in mathematics, science and engineering. Chaos, Solutions Fractals 26(2), 263–289 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  12. Hashemiparast, S.M., Hashemiparast, O.: Multi Parameters Golden Ratio and Some Applications. Appl. Math. 2(7), 808–815 (2011)

    Article  MathSciNet  Google Scholar 

  13. Wang, C.-Y., Li, L.-L., Yang, F.-P., Gong, H.: A new kind of adaptive weighted median filter algorithm. In: IEEE International Conference on Computer Application and System Modeling, vol. 11, pp. 667–671 (2010)

    Google Scholar 

  14. Iris Database: CASIA-IrisV1. http://biometrics.idealtest.org

Download references

Acknowledgements

The first and second author would like to thank UGC, New Delhi for the financial support received under UGC Major Research Project No. 43-274/2014(SR).

Author information

Authors and Affiliations

  1. Department of Computer Science, Periyar University, Salem, Tamilnadu, India

    K. Thangavel & K. Sasirekha

Authors
  1. K. Thangavel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K. Sasirekha
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to K. Thangavel .

Editor information

Editors and Affiliations

  1. Karpagam Academy of Higher Education, Coimbatore, India

    S. Subramanian

  2. PSG College of Technology, Coimbatore, India

    R. Nadarajan

  3. International Institute of Information Technology, Bengaluru, Karnataka, India

    Shrisha Rao

  4. Applied Mathematics and Computational Sciences, PSG College of Technology, Coimbatore, Tamil Nadu, India

    Shina Sheen

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Nature Singapore Pte Ltd.

About this paper

Cite this paper

Thangavel, K., Sasirekha, K. (2016). Denoising Iris Image Using a Novel Wavelet Based Threshold. In: Subramanian, S., Nadarajan, R., Rao, S., Sheen, S. (eds) Digital Connectivity – Social Impact. CSI 2016. Communications in Computer and Information Science, vol 679. Springer, Singapore. https://doi.org/10.1007/978-981-10-3274-5_5

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-3274-5_5

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3273-8

  • Online ISBN: 978-981-10-3274-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation