Skip to main content
SpringerLink
Log in

A Study on the Effective Approach to Illumination-Invariant Face Recognition Based on a Single Image

  • Conference paper
Book cover Biometric Recognition (CCBR 2012)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7701))

Included in the following conference series:

Abstract

In this paper, the methods for single image-based face recognition under varying lighting are reviewed. Meanwhile, some representative methods as well as their combinations are evaluated by experiments, and the underlying principle of the experimental results is investigated. According to our investigation, it is almost impossible to attain a satisfied face recognition result by using only one facial descriptor/representation especially under drastically varying illuminations. However, the “two-step” framework, including an illumination preprocessing and an illumination-insensitive facial features extraction, could be an effective approach to addressing this problem. We further study what are the appropriate illumination preprocessing and feature extraction for this framework.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adini, Y., Moses, Y., Ullman, S.: Face recognition: The problem of compensating for changes in illumination direction. IEEE TPAMI 19, 721–732 (1997)

    Article  Google Scholar 

  2. Phillips, P.J., et al.: Overview of the face recognition grand challenge. In: CVPR 2005 (2005)

    Google Scholar 

  3. Phillips, P., Moon, H., Rizvi, S., Rauss, P.: The FERET evaluation methodology for face-recognition algorithms. IEEE TPAMI 22, 1090–1104 (2000)

    Article  Google Scholar 

  4. Xie, X., Zheng, W.-S., Lai, J., Yuen, P.C., Suen, C.Y.: Normalization of Face Illumination Based on Large-and Small-Scale Features. IEEE TIP 20 (2011)

    Google Scholar 

  5. Zhang, T., Tang, Y.Y., Fang, B., Shang, Z., Liu, X.: Face recognition under varying illumination using gradientfaces. IEEE TIP 18, 2599–2606 (2009) (correspondence)

    MathSciNet  Google Scholar 

  6. Garcia, C., Zikos, G., Tziritas, G.: A wavelet-based framework for face recognition. In: Proc. ECCV 1998 (1998)

    Google Scholar 

  7. Okada, K., Steffens, J., Maurer, T., Hong, H., Elagin, E., Neven, H., Malsburg, C.: The bochum/USC face recognition system. In: Face Recogntion: From Theory to Applications, pp. 186–205. Springer, Berlin (1998)

    Google Scholar 

  8. Hafed, Z., Levine, M.: Face recognition using the discrete cosine transform. Int. J. Comput. Vis. 43, 167–188 (2001)

    Article  MATH  Google Scholar 

  9. Lai, J., Yuen, P.C., Feng, G.: Face recognition using holistic Fourier invariant features. Pattern Recognition 34, 95–109 (2001)

    Article  MATH  Google Scholar 

  10. Liu, C.-C., Dai, D.-Q.: Face recognition using dual-tree complex wavelet features. IEEE TIP 18, 2593–2599 (2009)

    MathSciNet  Google Scholar 

  11. Georghiades, A., Belhumeur, P., Kriegman, D.: From few to many: Illumination cone models for recognition under variable lighting and pose. IEEE TPAMI 23, 643–660 (2001)

    Article  Google Scholar 

  12. Shashua, A., Riklin-Raviv, T.: The quotient image: Class-based re-rendering and recognition with varying illuminations. IEEE TPAMI 23, 129–139 (2001)

    Article  Google Scholar 

  13. Basri, R., Jacobs, D.: Lambertian reflectance and linear subspaces. IEEE TPAMI 25, 218–233 (2003)

    Article  Google Scholar 

  14. Land, E.H., McCann, J.J.: Lightness and retinex theory. J. Opt. Soc. Amer. 61, 1–11 (1971)

    Article  Google Scholar 

  15. Jorstad, A., Jacobs, D., Trouvé, A.: A Deformation and Lighting Insensitive Metric for Face Recognition Based on Dense Correspondences. In: CVPR 2011 (2011)

    Google Scholar 

  16. Blanz, V., Vetter, T.: Face recognition based on fitting a 3D morphable model. IEEE TPAMI 25, 1063–1074 (2003)

    Article  Google Scholar 

  17. Zhao, W., Chellappa, R.: Symmetric shape-from-shading using self-ratio image. In: Proc. ICCV 2001 (2001)

    Google Scholar 

  18. Xie, X., Lam, K.: Face recognition under varying illumination based on a 2D face shape model. Pattern Recognition 38, 221–230 (2005)

    Google Scholar 

  19. Choi, S., Kim, C., Choi, C.-H.: Shadow compensation in 2D images for face recognition. Pattern Recognition 40, 2118–2125 (2007)

    Article  MATH  Google Scholar 

  20. Chen, W., Er, M., Wu, S.: Illumination compensation and normalization for robust face recognition using discrete cosine transform in logarithm domain. IEEE Trans. Syst., Man, Cybern. B. Cybern. 36, 458–466 (2006)

    Article  Google Scholar 

  21. Shashua, A., Riklin-Raviv, T.: The quotient image: Class-based re-rendering and recognition with varying illuminations. IEEE TPAMI 23, 129–139 (2001)

    Article  Google Scholar 

  22. Zhang, L., Wang, S., Samaras, D.: Face synthesis and recognition under arbitrary unknown lighting using a spherical harmonic basis morphable model. In: CVPR 2005 (2005)

    Google Scholar 

  23. Lee, J., Moghaddam, B., Pfister, H., Machiraju, R.: A bilinear illumination model for robust face recognition. In: ICCV 2005 (2005)

    Google Scholar 

  24. Qing, L., Shan, S., Gao, W., Du Face, B.: recognition under generic illumination based on harmonic relighting. Int. J. Pattern Recognit. Artif. Intell. 19, 513–531 (2005)

    Article  Google Scholar 

  25. Shim, H., Luo, J., Chen, T.: A subspace model-based approach to face relighting under unknown lighting and poses. IEEE TIP 17, 1331–1341 (2008)

    MathSciNet  Google Scholar 

  26. Chen, T., Yin, W., Zhou, X., Comaniciu, D., Huang, T.S.: Total variation models for variable lighting face recognition. IEEE TPAMI 28, 1519–1524 (2006)

    Article  Google Scholar 

  27. Wang, B., Li, W., Yang, W., Liao, Q.: Illumination Normalization Based on Weber’s Law with Application to Face Recognition. IEEE Signal Processing Letter 18, 462–465 (2011)

    Article  Google Scholar 

  28. Tan, X., Triggs, B.: Enhanced local texture feature sets for face recognition under difficult lighting conditions. IEEE TIP 19, 1635–1650 (2010)

    MathSciNet  Google Scholar 

  29. Wang, H., Li, S.Z., Wang, Y., Zhang, J.: Self quotient image for face recognition. In: Image Processing, ICIP 2004 (2004)

    Google Scholar 

  30. Xie, X., Lai, J., Zheng, W.-S.: Extraction of Illumination Invariant Facial Features from a Single Image Using Nonsubsampled Contourlet Transform. Pattern Recognition 43, 4177–4189 (2010)

    Article  MATH  Google Scholar 

  31. Zhang, T., Fang, B., Yuan, Y., Tang, Y., Shang, Z., Li, D., Lang, F.: Multiscale facial structure representation for face recognition under varying illumination. Pattern Recognition 42, 251–258 (2009)

    Article  MATH  Google Scholar 

  32. Xuan, Z., Kittler, J., Messer, K.: Illumination Invariant Face Recognition: A Survey. In: IEEE International Conference on Biometrics: Theory, Applications, and Systems (2007)

    Google Scholar 

  33. Ahonen, T., Hadid, A., Pietikainen, M.: Face description with local binary patterns: Application to face recognition. IEEE TPAMI 28(12) (2006)

    Google Scholar 

  34. Phillips, P.J., et al.: Overview of the face recognition grand challenge. In: CVPR 2005 (2005)

    Google Scholar 

  35. Sim, T., Baker, S., Bsat, M.: The CMU Pose, Illumination, and Expression (PIE) Database. In: Proc. Conf. Automatic Face and Gesture Recognition, Washington (2002)

    Google Scholar 

  36. Amirhosein, N., Esam, A.-R., Majid, A.: Illumination invariant feature extraction and mutual-information-based local matching for face recognition under illumination variation and occlusion. Pattern Recognition 44, 2576–2587 (2011)

    Article  Google Scholar 

  37. Chen, L.-H., Yang, Y.-H., Chen, C.-S., Cheng, M.-Y.: Illumination Invariant Feature Extraction Based on Natural Images Statistics – Taking Face Images as An Example. In: CVPR 2011 (2011)

    Google Scholar 

  38. Schroff, F., Treibitz, T., Kriegman, D.J., Belongie, S.: Pose, illumination and expression invariant pairwise face-similarity measure via Doppelgänger list comparison. In: ICCV 2011 (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055, China

    Jiapei Zhang & Xiaohua Xie

  2. Shenzhen Key Laboratory for Visual Computing and Analytics, Shenzhen, 518055, China

    Jiapei Zhang & Xiaohua Xie

Authors
  1. Jiapei Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaohua Xie
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Information Science and Technology, Sun Yat-Sen University, 510275, Guangzhou, P.R. China

    Wei-Shi Zheng  & Jianhuang Lai  & 

  2. Institute of Automation, National Laboratory of Pattern Recognition, Chinese Academy of Sciences, 100190, Beijing, P.R. China

    Zhenan Sun

  3. School of Computer Science and Engineering, Beihang University, Beijing University of Aeronautics and Astronautics, 100191, Beijing, P.R. China

    Yunhong Wang

  4. Institute of Computing Technology, Chinese Academy of Sciences, 100190, Beijing, P.R. China

    Xilin Chen

  5. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Kowloon, Hong Kong, China

    Pong C. Yuen

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhang, J., Xie, X. (2012). A Study on the Effective Approach to Illumination-Invariant Face Recognition Based on a Single Image. In: Zheng, WS., Sun, Z., Wang, Y., Chen, X., Yuen, P.C., Lai, J. (eds) Biometric Recognition. CCBR 2012. Lecture Notes in Computer Science, vol 7701. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35136-5_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-35136-5_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35135-8

  • Online ISBN: 978-3-642-35136-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation