Skip to main content
SpringerLink
Log in
Book cover

Artificial Intelligence and Evolutionary Computations in Engineering Systems pp 473–483Cite as

Edge Feature Extraction of X-Ray Images Based on Simplified Gabor Wavelet Transform

  • Conference paper
  • First Online:

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 668))

Abstract

Noadays, X-ray images play vital role in the field of medicine. The edge feature extraction technique which helps medical practitioners to detect the minute factures as it may not be possible by the necked eye. The edge feature extraction methods deals with detection of edges of an image. There are several wavelet-based methods to extract the features of an edge. The conventional Gabor Wavelet is a complex wavelet which is extensively used for edge feature extraction. This conventional Gabor wavelet may not be useful for real-time applications due to high-computational complexity. So simplified Gabor wavelet transform is used instead of conventional Gabor wavelet. It is a very efficient technique to detect location and orientation of edges. The proposed simplified Gabor wavelet transform performs well for the edge feature extraction in comparison with conventional Gabor wavelet, orthogonal and biorthogonal wavelets.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
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

References

  1. S.K. Mahendran, S. Santhosh Baboo, in Enhanced Automatic X-Ray Bone Image Segmentation using wavelets and Morphological Operators. 2011 International Conference on Information and Electronics Engineering IPCSIT, vol. 6 (IACSIT Press, Singapore, 2011)

    Google Scholar 

  2. P.S. Addison, in The Illustrated Wavelet Transform Handbook. IOP publishing Ltd 2002

    Google Scholar 

  3. Lei Lizhen, Discussion of digital image edge detection method. Mapping Aviso 3, 40–42 (2006)

    Google Scholar 

  4. F.y. Cui, L.J. Zou, B. Song, in Edge Feature Extraction Based on Digital Image Processing Techniques. Proceedings of the IEEE, International Conference on Automation and Logistics, (Qingdao, China Sept 2008), pp. 2320–2324

    Google Scholar 

  5. R.C. Gonzalez, R.E. Woods, in Digital Image Processing, 2nd edn. (Prentice Hall Publications, 1992)

    Google Scholar 

  6. R.C. Gonzalez, R.E. Woods, in Digital Image Processing Using MATLAB, 2nd edn. (Paretice Hall India Limited, 1992)

    Google Scholar 

  7. P.M.K. Prasad, G. Sasi Bhushana Rao, M.N.V.S.S. Kumar, in Analysis of X-Ray images using MRA based Biorthogonal wavelets for detection of minute fractures. International Conference on Science, Engineering and Management Research (ICSEMR 2014) IEEE

    Google Scholar 

  8. W. Jiang, K.M. Lam, T.Z. Shen, Efficient edge detection using simplified gabor wavelets. IEEE Trans. Syst. Man Cybern. Part: Cybern. 39(4), Aug 2009

    Google Scholar 

  9. L. Debnath, Wavelet Transforms & Their Application. (Birkhauser Boston, 2002)

    Google Scholar 

  10. K.P. Soman, K. I. Ramachandran, Insight Into wavelets from theory to Practice, 2nd edn. (Prentice Hall of India, 2008)

    Google Scholar 

  11. H. Cheng, N. Zheng, C. Sun, in Boosted Gabor Features Applied to Vehicle Detection. 18th International (A.3) Conference on Pattern Recognition, pp. 662–666, 2006

    Google Scholar 

  12. R. Mehrotra, K.R. Namuduri, N. Ranganthan, Gabor filter-based edge detection. Pattern Recogn. 25, 1479–1494 (1992)

    Article  Google Scholar 

  13. W.P. Choi, S.H. Tse, K.W. Wong, K.M. Lam, Simplified gabor wavelets for human face recognition. Pattern Recogn. 41, 1186–1199 (2008)

    Article  MATH  Google Scholar 

  14. S.M. Salve, Mammographic image classification using gabor wavelet. Int. Res. J. Eng. Technol. 03(03), pp. 202–207, 03 Mar 2016, ISSN: 2395-0072

    Google Scholar 

  15. C. Liu, H. Wechsler, Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition. IEEE Trans. Image Process. 11, 467–476 (2002)

    Article  Google Scholar 

  16. H. Cheng, N. Zheng, C. Sun, Boosted Gabor Features Applied to Vehicle Detection. Proceedings 18th International Conference Pattern Recognition, vol. 1, pp. 662–666, 2006

    Google Scholar 

  17. W. Jiang, T.Z. Shen, J. Zhang, Y.Hu, X.Y. Wang, in Gabor Wavelets for Image Processing. IEEE International Colloquium on Computing, Communication, Control, and Management, vol. 1, pp.110–114, 2008

    Google Scholar 

  18. X. Xie, K.M. Lam, Gabor-based kernel PCA with doubly nonlinear mapping for face recognition with a single face image. IEEE Trans. Image Process. 15(9), 2481–2492 (2006)

    Article  Google Scholar 

  19. R. Mehrotra, K.R. Namuduri, N. Ranganthan, Gabor filter-based edge detection. Pattern Recognit. 25(12), 1479–1494 (1992)

    Article  Google Scholar 

  20. Y.P. Guan, Automatic extraction of lips based on multi-scale wavelet edge detection. Comput. Vis. 2(1), 23–33, (2008)

    Google Scholar 

  21. W. Jiang, K.M. Lam, T.Z. Shen, in Edge Detection Using Simplified Gabor Wavelets. IEEE International Conference Neural Networks & Signal Processing Zhenjiang, China, June 8, 2008

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of E.C.E, G.V.P. College of Engineering for Women, Visakhapatnam, India

    P. M. K. Prasad

  2. Department of E.C.E, JNTUH College of Engineering, Jagityal, Telengana, India

    Y. Raghavender Rao

Authors
  1. P. M. K. Prasad
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Y. Raghavender Rao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to P. M. K. Prasad .

Editor information

Editors and Affiliations

  1. Electrical and Electronics Engineering, SRM Engineering College, Kattankulathur, Tamil Nadu, India

    Subhransu Sekhar Dash

  2. Department of Electrical and Electronics Engineering, Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh, India

    Paruchuri Chandra Babu Naidu

  3. Department of Electrical and Electronics Engineering, Gazi University, Ankara, Turkey

    Ramazan Bayindir

  4. Indian Statistical Institute, Kolkata, India

    Swagatam Das

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Prasad, P.M.K., Raghavender Rao, Y. (2018). Edge Feature Extraction of X-Ray Images Based on Simplified Gabor Wavelet Transform. In: Dash, S., Naidu, P., Bayindir, R., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 668. Springer, Singapore. https://doi.org/10.1007/978-981-10-7868-2_46

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-7868-2_46

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7867-5

  • Online ISBN: 978-981-10-7868-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation