Skip to main content

Advertisement

Springer Nature Link
Log in

Reduced quaternion matrix for color texture classification

  • Original Article
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

As a newly developed singular value decomposition of the reduced quaternion matrix (SVDRQ), the two reduced quaternion unitary matrices can effectively capture the intrinsic geometric structures and smooth contours of color texture image. The projection vector by the two unitary matrices is used as dominant features for color texture classification. In this paper, we proposed new algorithm to implement the computation of the SVDRQ, and then proposed new color texture classification scheme based on SVDRQ, the Euclidean distance is applied as classifier in the proposed scheme. It is demonstrated by the experiments that our proposed scheme significantly improves the color texture classification accuracy in comparison with several conventional texture classification approaches.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Explore related subjects

Discover the latest articles and news from researchers in related subjects, suggested using machine learning.

References

  1. Sertel O, Kong J, Catalyurek UV, Lozanski G (2009) Histopathological image analysis using model-based intermediate representations and color texture: follicular lymphoma grading. Signal Process 55(1–3):169–183

    Google Scholar 

  2. Maia E, Hammouch H, Aboutajdine A (August 2009) Color-texture analysis by mutual information for multispectral image classification. In: International conference on communications, computers and signal processing, Canada, pp 359–364

  3. Martinez A, Delgado JL, Balibrea JD (2005) Automatic system for quality-based classification of marble textures. IEEE Trans Syst Man Cybern 35(4):488–497

    Google Scholar 

  4. Li Z, Liu Y, Walker R (2010) Color and texture feature fusion using kernel PCA with application to object-based vegetation species classification. IEEE Conf Image Process 8:2701–2704

    Google Scholar 

  5. Van de Wouwe G, Scheunders P, Livens S, Van Dyck D (1999) Wavelet correlation signatures for color texture characterization. Pattern Recogn 32(3):443–451

    Article  Google Scholar 

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

    Article  Google Scholar 

  7. Ojala T, Pietikainen M, Maenpaa T (2002) Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans Pattern Anal Mach Intell 24(7):971–987

    Article  Google Scholar 

  8. Palm C (2004) Color texture classification by integrative co-occurrence matrices. Pattern Recogn 37(5):965–976

    Article  Google Scholar 

  9. Zhang C, Sun DW, Zheng L (2007) A new region-primitive method for classification of color meat image texture based size, orientation and contrast. Meat Sci 76(4):620–627

    Article  Google Scholar 

  10. Dong YS, Ma JW (2011) Wavelet-based image texture classification using local energy histograms. IEEE Trans Signal Process Lett 18(4):247–250

    Article  Google Scholar 

  11. Si ZZ, Zhu SC (2012) Learning hybrid image templates (HIT) by information projection. IEEE Trans Pattern Anal Mach Intell 34(7):1354–1367

    Article  Google Scholar 

  12. Zhao CR, Liu CC, Lai ZH (2011) Multi-scale gist feature manifold for building recognition. Neurocomputing 74(17):2929–2940

    Article  Google Scholar 

  13. Zhao CR, Lai ZH, Liu CC, Gu XJ, Qian JJ (2012) Fuzzy local maximal marginal embedding for feature extraction. Soft Comput 16(1):77–87

    Article  Google Scholar 

  14. Zhao CR, Miao DQ, Lai ZH, Gao C, Liu CC, Yang JY (2013) Two-dimensional color uncorrelated discriminant analysis for face recognition. Neurocomputing 113(3):251–261

    Article  Google Scholar 

  15. Lai ZH, Wan MH, Jin Z, Yang J (2011) Sparse two-dimensional local discriminant projections for feature extraction. Neurocomputing 74(4):629–637

    Article  Google Scholar 

  16. Lai ZH, Zhao CR, Wan MH (2012) Fisher difference discriminant analysis: determining the effective discriminant subspace dimensions for face recognition. Neural Process Lett 35(3):203–220

    Article  Google Scholar 

  17. Choi JY, Ro YM, Plataniotis KN (2012) Color local texture features for color face recognition. IEEE Trans Image Process 21(3):1366–1380

    Article  MathSciNet  Google Scholar 

  18. Hamilton WR (1866) Elements of quaternions. Longmans, Green and London

    Google Scholar 

  19. Daniel C, Weiss H, Bar IY (2012) Quaternion estimation from vector observations using a matrix Kalman filter. IEEE Trans Aerosp Electron Syst 48(4):3133–3158

    Article  Google Scholar 

  20. Javier V, Palomar DP, Luis V, Ignacio S (2011) Quaternion ICA from second-order statistics. IEEE Trans Signal Process 59(4):1586–1600

    Article  Google Scholar 

  21. Amir K, Pecht Y, Orly (2011) Quaternion structural similarity: a new quality index for color images. IEEE Trans Image Process 21(4):1526–1536

    Google Scholar 

  22. Bihan NL, Sangwine SJ (2007) Jacobi method for quaternion matrix singular value decomposition. Appl Math Comput 187(2):1265–1271

    Article  MATH  MathSciNet  Google Scholar 

  23. Wang QW, Li CK (2009) Ranks and the least-norm of the general solution to a system of quaternion matrix equations. Linear Algebra Appl 430(5–6):1626–1640

    Article  MATH  MathSciNet  Google Scholar 

  24. Sun YF, Chen SY, Yin B (2011) Color face recognition based on quaternion matrix representation. Pattern Recogn Lett 32(4):597–606

    Article  Google Scholar 

  25. Bihan NL, Mars J (2004) Singular value decomposition of quaternion matrices: a new tool for vector-sensor signal processing. Signal Process 84(7):1177–1199

    Article  MATH  Google Scholar 

  26. Menanno GM, Bihan NL (2010) Quaternion polynomial matrix diagonalization for the separation of polarized convolutive mixture. Signal Process 90(7):2219–2231

    Article  MATH  Google Scholar 

  27. Wang QW, Yu SW, Lin CY (2008) Extreme ranks of a linear quaternion matrix expression subject to triple quaternion matrix equations with applications. Appl Math Comput 195(2):733–744

    Article  MATH  MathSciNet  Google Scholar 

  28. Database VisTex of color textures of MIT, USA. ftp://whitechape.media.mit.edu/pub/VisTex

  29. Database of color textured barks of University of Koblenz Germany. ftp://ftphost.uni-koblenz.de/outgoing/vision/Lakmann/BarkTex

  30. Lakmann R (1998) Statistische Modellierung von Farbtexturen, Ph.D. Thesis, University Koblenz-Landau, Folbach, Koblenz; in German

Download references

Acknowledgments

This work is partially supported by National Natural Science Foundation of China (61202319, 61272077, 61203243, 61162002); Department of Education of Jiangxi (GJJ13481); China Postdoctoral Science Foundation under Grant No. 2013M530224, 2013M530223. Open fund of Image Processing and Pattern Recognition under Grant No. TX201304001.

Author information

Authors and Affiliations

  1. Key Laboratory of Image Processing and Pattern Recognition, Nanchang Hangkong University, Nanchang, 330063, Jiangxi, China

    Shan Gai, Minghua Wan, Lei Wang & Cihui Yang

Authors
  1. Shan Gai
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Minghua Wan
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Lei Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Cihui Yang
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Shan Gai.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gai, S., Wan, M., Wang, L. et al. Reduced quaternion matrix for color texture classification. Neural Comput & Applic 25, 945–954 (2014). https://doi.org/10.1007/s00521-014-1578-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-014-1578-0

Keywords