Skip to main content
SpringerLink
Log in

Rotation Invariant Texture Retrieval Using Dual Tree Complex Wavelet Transform

  • Conference paper
  • First Online:
Soft Computing Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 357))

Abstract

Texture automatic identification continues to be a challenge in the attempt of object detection and content-based image recognition. While the human eye easily detects various textures, edges, shapes, and objects, the situation is much more complicated for computer-based systems. Images are rarely taken from identical positions, thus, there is an obvious variance in the texture image content. One of the important issues to be solved is rotation invariant texture analysis, actually studied under various methods. Our attempt is based on a new rotated texture analysis using Dual Tree Complex Wavelet Transform (DTCWT). We apply a geometrical transform to the image before extracting the texture characteristics. The feature vectors consist of the mean of the coefficients computed with the DTCWT. Sorting the feature vectors before comparing them is an important stage toward rotation invariance. Our tests proved to return high-accuracy rotated texture retrieval rates (100 % for a dataset with 13 texture images and up to 98.5 % for 112 textures), better than other reported results.

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

Access this chapter

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

Institutional subscriptions

References

  1. Pratt William K (2007) Digital image processing: piks scientific inside, Wiley-Interscience, 4th edn. Wiley, New Jersey

    Book  Google Scholar 

  2. Pickett RM (1970) Visual analysis of texture in the detection and recognition of objects. In: Lipkin BC, Rosenfeld A (eds) Picture processing and psychopictorics. Academic Press, NewYork, pp 289–308

    Google Scholar 

  3. Hawkins JK (1970) Textural properties for pattern recognition. In: Lipkin BC, Rosenfeld A (eds) Picture processing and psychopictorics. Academic Press, NewYork, pp 347–370

    Google Scholar 

  4. Haralick RM (1979) Statistical and structural approaches to texture. Proc IEEE 67(5):786–804

    Article  Google Scholar 

  5. Davis LS (1981) Polarogram: a new tool for image texture analysis. Pattern Recogn 13(3):219–223

    Article  Google Scholar 

  6. Rao AR (1990) A taxonomy for texture description and identification. Springer, Berlin

    Book  MATH  Google Scholar 

  7. Tuceryan M, Jain AK (1993) Texture analysis, In: Chen CH, Pau LF, Wang PSP (eds) Handbook of pattern recognition and computer vision, 1993, World Scientific Publishing, pp 235–276

    Google Scholar 

  8. Reed TR, Du Buf JMH (1993) A review of recent texture segmentation and feature extraction techniques. CVGIP: Image Understanding 57:359–372

    Article  Google Scholar 

  9. Petrou M, Sevilla PG (2006) Image processing: dealing with texture. Wiley, England

    Book  Google Scholar 

  10. Mirmehdi M, Xie X, Suri J (eds) (2008) Handbook of texture analysis. Imperial College Press, London

    Google Scholar 

  11. Kingsbury NG (1998) The dual-tree complex wavelet transform: a new technique for shift invariance and directional filters. In: Proceedings of 8th IEEE DSP workshop, Utah, 9–12 Aug 1998, paper no 86

    Google Scholar 

  12. Kingsbury NG (1998) The dual-tree complex wavelet transform: a new efficient tool for image restoration and enhancement. In: Proceedings of European signal processing Conference, Rhodes, Sept 1998, pp 319–322

    Google Scholar 

  13. Selesnick IW, Baraniuk RG, Kingsbury NG (2005) The dual tree complex wavelet transform DTCWT. IEEE Signal Process Mag 22(6):123–151

    Article  Google Scholar 

  14. Costin M, Ignat A, (2011) Pitfalls in using dual tree complex wavelet transform for texture featuring: a discussion. In: IEEE WISP 2011—7th IEEE international symposium on intelligent signal processing, Floriana, Malta, 19–21 Sept 2011, pp 110–115

    Google Scholar 

  15. Ignat A, Luca M, Ciobanu A (2013) Iris features using dual tree complex wavelet transform in texture evaluation for biometrical identification. In: 4th IEEE international conference on e-health and bioengineering—EHB 2013, Iaşi, Romania, 21–23 noiembrie 2013

    Google Scholar 

  16. Zhang J, Tan T (2002) Brief review of invariant texture analysis methods. Pattern Recogn 35:735–747, Elsevier, PERGAMON Press

    Google Scholar 

  17. Sifre L, Mallat S (2012) Combined scattering for rotation invariant texture analysis, ESANN 2012. In: European symposium on artificial neural networks, computational intelligence and machine learning, Bruges (Belgium), 25–27 April 2012

    Google Scholar 

  18. Rahman MH, Pickering MR, Frater MR (2011) Scale and rotation invariant Gabor features for texture retrieval. In: DICTA ‘11 Proceedings of the 2011 international conference. on digital image computing: techniques and applications, Noosa, QLD, Australia, 6–8 Dec 2011, pp 602–607

    Google Scholar 

  19. Lo EHS, Pickering M, Frater M, Arnold J (2004) Scale and rotation invariant texture features from the dual-tree complex wavelet transform. In: IEEE proceedings of the international conference on image processing (ICIP), vol 1. Singapore, 24–27 Oct 2004, pp 227–230

    Google Scholar 

  20. Chen S, Shang Y, Mao B, Lian Q (2007) Rotation invariant texture classification algorithm based on DT–CWT and SVM. In: Proceedings of the 4th international symposium on neural networks advances in neural networks, ISNN‘07 Part III, June, 2007. Nanjing, China, pp 454–460

    Google Scholar 

  21. Mayorga M, Ludman L (1994) Shift and rotation invariant texture recognition with neural nets. In: Proceedings of IEEE international conference on neural networks, 1994, pp 4078–4083

    Google Scholar 

  22. Hill PR, Bull DR, Canagarajah CN (2000) Rotationally invariant texture features using the dual-tree complex wavelet transform. In: IEEE proceedings of the international conference on image processing (ICIP), vol 3, Vancouver, Canada, 2000, pp 901–904

    Google Scholar 

  23. Kingsbury NG (2001) Complex wavelets for shift invariant analysis and filtering of signals. J Appl Comput Harmonic Anal 3:234–253

    Article  MathSciNet  Google Scholar 

  24. Kingsbury NG (2003) Design of Q-shift complex wavelets for image processing using frequency domain energy minimization. In: Proceedings IEEE conference on image processing. Barcelona, 15–17 Sept 2003, paper 1199

    Google Scholar 

  25. Hatipoglu S, Mitra SK, Kingsbury NG (2000) Image texture description using complex wavelet transform. In: Proceedings of IEEE international conference on image processing, vol 2, Vancouver, BC, Canada, Sept 2000, pp 530–533

    Google Scholar 

  26. Hatipoglu S, Mitra SK, Kingsbury N (1999) Texture classification using dual-tree complex wavelet transform. IEEE Image Proc Appl. 465:344–347

    Google Scholar 

  27. Celik T, Tjahadi T (2009) Multiscale texture classification using dual-tree complex wavelet transform. Pattern Recogn Lett 30:331–339

    Article  Google Scholar 

  28. Wang H-Z, He X-H, Zai W-J, (2007) Texture image retrieval using dual-tree complex wavelet transform. In: Proceedings of the 2007 international conference on wavelet analysis and pattern recognition, Beijing, China, 2–4 Nov 2007, pp 230–234

    Google Scholar 

  29. Mumtaz A, Gilani SAM, Hameed K, Jameel T (2008) Enhancing performance of image retrieval systems using dual tree complex wavelet transform and support vector machines. J Comput Inf Technol 16(1):57–68

    Google Scholar 

  30. Liao B, Peng F (2010) Rotation-invariant texture features extraction using dual-tree complex wavelet transform. In: International conference on information, networking and automation (ICINA), Kunming, China, 18–19 Oct 2010, pp VI-361–VI-364

    Google Scholar 

  31. Brodatz P (2014) Textures: a photographic album for artists and designers, Dover, N.Y., USA, Accessed March 2014. http://www.ux.uis.no/~tranden/brodatz.html

  32. Kingsbury’s (2014) web page. Accessed May 2014. http://www-sigproc.eng.cam.ac.uk/Main/NGK

  33. Brodatz—new. http://multibandtexture.recherche.usherbrooke.ca/index.html

Download references

Author information

Authors and Affiliations

  1. Faculty of Computer Science, “Alexandru Ioan Cuza” University of Iasi, Iaşi, Romania

    Anca Ignat

  2. Institute of Computer Science, Romanian Academy, Iaşi, Romania

    Mihaela Luca

Authors
  1. Anca Ignat
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mihaela Luca
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anca Ignat .

Editor information

Editors and Affiliations

  1. Department of Automation and Applied Informatics, Aurel Vlaicu University of Arad Faculty of Engineering, Arad, Romania

    Valentina Emilia Balas

  2. Faculty of Science and Technology, Data Science Institute, Bournemouth University, Poole, United Kingdom

    Lakhmi C. Jain

  3. University of Belgrade, Belgrade, Serbia

    Branko Kovačević

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Ignat, A., Luca, M. (2016). Rotation Invariant Texture Retrieval Using Dual Tree Complex Wavelet Transform. In: Balas, V., Jain, L., Kovačević, B. (eds) Soft Computing Applications. Advances in Intelligent Systems and Computing, vol 357. Springer, Cham. https://doi.org/10.1007/978-3-319-18416-6_71

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-18416-6_71

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18415-9

  • Online ISBN: 978-3-319-18416-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation