Skip to main content
SpringerLink
Log in
Book cover

International Conference on Intelligent Computing

ICIC 2017: Intelligent Computing Theories and Application pp 177–189Cite as

Color Two-Dimensional Principal Component Analysis for Face Recognition Based on Quaternion Model

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10361))

Abstract

The color two-dimensional principal component analysis (color 2DPCA) approach based on quaternion model is presented for color face recognition. Based on 2D quaternion matrices rather than 1D quaternion vectors, color 2DPCA combines the color information and the spatial characteristic for face recognition, and straightly computes the low-dimensional covariance matrix of the training color face images and determines the corresponding eigenvectors in a short CPU time. The image reconstruction theory is also built on color 2DPCA. The experiments on real face data sets are provided to validate the feasibility and effectiveness of the proposed algorithm.

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   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
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. Belhumeur, P.N., Hespanha, J.P., Kriengman, D.J.: Eigenfaces vs. Fisherfaces: recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell. 19(7), 711–720 (1997)

    Article  Google Scholar 

  2. Bihan, N.L., Sangwine, S.J.: Quaternion principal component analysis of color images. In: Image Processing, pp. 809–810 (2003)

    Google Scholar 

  3. Denis, P., Carre, P., Fernandez-Maloigne, C.: Spatial and spectral quaternionic approaches for colour images. Comput. Vis. Image Underst. 107, 74–87 (2007)

    Article  Google Scholar 

  4. Hamilton, W.R.: Elements of Quaternions. Chelsea, New York (1969)

    Google Scholar 

  5. Kirby, M., Sirovich, L.: Application of the karhunenloeve procedure for the characterization of human faces. IEEE Trans. Pattern Anal. Mach. Intell. 12(1), 103–108 (1990)

    Article  Google Scholar 

  6. Luo, Y., Chen, D.: Face recognition based on color Gabor features. J. Image Graph. 13(2), 242–243 (2006)

    Google Scholar 

  7. Pei, S.-C., Chang, J.-H., Ding, J.-J.: Quaternion matrix singular value decomposition and its applications for color image processing. In: Image Processing, ICIP 2003, vol. 1, pp. 805–808 (2003)

    Google Scholar 

  8. Pentland, A.: Looking at people: sensing for ubiquitous and wearable computing. IEEE Trans. Pattern Anal. Mach. Intell. 22(1), 107–119 (2000)

    Article  Google Scholar 

  9. Qiao, L., Chen, S., Tan, X.: Sparsity preserving discriminant analysis for single training image face recognition. Pattern Recogn. Lett. 31, 422–429 (2010)

    Article  Google Scholar 

  10. Qiao, L., Chen, S., Tan, X.: Sparsity preserving projections with applications to face recognition. Pattern Recogn. 43, 331–341 (2010)

    Article  MATH  Google Scholar 

  11. Shi, L., Funt, B.: Quaternion color texture segmentation. Comput. Vis. Image Underst. 107, 88–96 (2007)

    Article  Google Scholar 

  12. Sangwine, S., Bihan, N.L.: Quaternion toolbox for Matlab. http://qtfmsourceforge.net/

  13. Sinha, P., et al.: Face recognition by humans: nineteen results all computer vision researchers should know about. In: Proceedings of the IEEE, vol. 94(11), pp. 1948–1962 (2006)

    Google Scholar 

  14. Sirovich, L., Kirby, M.: Low-dimensional procedure for characterization of human faces. J. Optical Soc. Am. 4, 519–524 (1987)

    Article  Google Scholar 

  15. Torres, L., Reutter, J.Y., Lorente, L.: The importance of the color information in face recognition. In: IEEE International Conference on Image Processing, vol. 3, pp. 627–631 (1999)

    Google Scholar 

  16. Turk, M., Pentland, A.: Eigenfaces for recognition. J. Cogn. Neurosci. 3(1), 71–76 (1991)

    Article  Google Scholar 

  17. Xiang, X., Yang, J., Chen, Q.: Color face recognition by PCA-like approach. Neurocomputing 152, 231–235 (2015)

    Article  Google Scholar 

  18. Yang, J., Zhang, D., Frangi, A.F., Yang, J.Y.: Two-dimensional PCA: a new approach to appearance-based face representation and recognition. IEEE Trans. Pattern Anal. Mach. Intell. 26(1), 131–137 (2004)

    Article  Google Scholar 

  19. Yang, J., Liu, C.: A general discriminant model for color face recognition. In: IEEE 11th International Conference on Computer Vision, pp. 1–6 (2007)

    Google Scholar 

  20. Zhang, F.: Quaternions and matrices of quaternions. Linear Algebra Appl. 251, 21–57 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  21. Zhao, L., Yang, Y.: Theoretical analysis of illumination in PCA-based vision systems. Pattern Recogn. 32(4), 547–564 (1999)

    Article  Google Scholar 

  22. The Georgia Tech face database. http://www.anefian.com/research/facereco.htm

  23. The LFW face database. http://www.cs.umass.edu/lfw

Download references

Acknowledgment

We are grateful to four anonymous referees for their excellent comments on the manuscript, which helped us to improve the paper. This paper is supported by National Natural Science Foundation of China under grant 11201193 and 11301529, TAPP (PPZY2015A013) and PAPD of Jiangsu Higher Education Institutions.

Author information

Authors and Affiliations

  1. School of Mathematics and Statistics, Jiangsu Key Laboratory of Education Big Data Science and Engineering, Jiangsu Normal University, Xuzhou, 221116, China

    Zhi-Gang Jia & Mei-Xiang Zhao

  2. School of Mathematics, China University of Mining and Technology, Xuzhou, 221116, China

    Si-Tao Ling

  3. School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, 221116, China

    Mei-Xiang Zhao

Authors
  1. Zhi-Gang Jia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Si-Tao Ling
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mei-Xiang Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhi-Gang Jia .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Politecnico di Bari, Bari, Italy

    Vitoantonio Bevilacqua

  3. University of Wollongong, North Wollongong, New South Wales, Australia

    Prashan Premaratne

  4. Indian Institute of Technology, Kanpur, India

    Phalguni Gupta

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Jia, ZG., Ling, ST., Zhao, MX. (2017). Color Two-Dimensional Principal Component Analysis for Face Recognition Based on Quaternion Model. In: Huang, DS., Bevilacqua, V., Premaratne, P., Gupta, P. (eds) Intelligent Computing Theories and Application. ICIC 2017. Lecture Notes in Computer Science(), vol 10361. Springer, Cham. https://doi.org/10.1007/978-3-319-63309-1_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-63309-1_17

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63308-4

  • Online ISBN: 978-3-319-63309-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation