Skip to main content
SpringerLink
Log in

A Hardware-Directed Face Recognition System Based on Local Eigen-analysis with PCNN

  • Conference paper
Book cover Neural Information Processing (ICONIP 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3316))

Included in the following conference series:

Abstract

A new face recognition system based on eigenface analysis on segments of face images is discussed in this paper. The eigenfaces are extracted using principal component neural networks. The proposed recognition system can tolerate local variations in the face such as expression changes and directional lighting. Further, the system can be easily mapped onto the hardware.

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. Turk, M.A., Pentland, A.P.: Eigenfaces for recognition. Journal of Cognitive Neuroscience 3(1), 71–86 (1991)

    Article  Google Scholar 

  2. Lemieus, A., Parizeau, M.: Experiments on eigenfaces robustness. Proceedings of IEEE International Conference on Pattern Recognition 1, 421–424 (2002)

    Google Scholar 

  3. Turk, M.A., Pentland, A.P.: Face recognition using eigenfaces. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 586–591 (1991)

    Google Scholar 

  4. Waldoestl, D., Lizama, E., Nickolay, B.: An eigenfaces-based automatic face recognition system. In: Proceedings of IEEE International Conference on Systems, Man and Cybernetics, pp. 174–177 (1997)

    Google Scholar 

  5. Zhujie, Yu, Y.L.: Face recognition with eigenfaces. In: Proceedings of IEEE International Conference on Industrial Technology, December 1994, pp. 434–438 (1994)

    Google Scholar 

  6. Haykin, S.: Neural networks: A comprehensive foundation. Prentice Hall India, Englewood Cliffs (1999)

    MATH  Google Scholar 

  7. Diamantaras, K.I., Kung, S.Y.: Principal component neural networks:Theory and applications. Wiley, New York (1996)

    MATH  Google Scholar 

  8. Sanger, T.D.: Optimal unsupervised learning in a single layer feedforward neural network. Neural Networks 2, 459–473 (1989)

    Article  Google Scholar 

  9. Oja, E.: A simplified neuron model as a principal component analyzer. Journal of Mathematical Biology 15, 267–273 (1982)

    Article  MATH  MathSciNet  Google Scholar 

  10. Oja, E., Karhunen, J.: On stochastic approximation of the eigen vectors and eigen values of the expectation of a random matrix. Journal of Mathematical Analysis and Applications 104, 69–84 (1985)

    Article  MathSciNet  Google Scholar 

  11. Costa, S., Fiori, S.: Image compression using Principal component neural networks. Image and Vision Computing Journal 19, 649–668 (2001)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. VLSI Laboratory, Department of Computer Science and Engineering, Indian Institute of Technology Madras, Chennai, 600 036, India

    C. Siva Sai Prasanna, N. Sudha & V. Kamakoti

Authors
  1. C. Siva Sai Prasanna
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. N. Sudha
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. V. Kamakoti
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Indian Statistical Institute, Electronics and Communication Sciences Unit, Kolkata, India

    Nikhil Ranjan Pal

  2. School of Computer and Information Sciences, Knowledge Engineering and Discovery Research Institute (KEDRI), Auckland University of Technology, Private Bag 92006, Auckland, New Zealand

    Nik Kasabov

  3. Department of Instrumentation and Electronics Engineering, Jadavpur University, Salt-lake Campus, 700098, Calcutta, India

    Rajani K. Mudi

  4. Indian Statistical Institute, 203 B. T. Road, 700 108, Calcutta,  

    Srimanta Pal

  5. Indian Statistical Institute, Computer Vision and Pattern Recognition Unit, 700108, Kolkata, India

    Swapan Kumar Parui

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Prasanna, C.S.S., Sudha, N., Kamakoti, V. (2004). A Hardware-Directed Face Recognition System Based on Local Eigen-analysis with PCNN. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_49

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-30499-9_49

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23931-4

  • Online ISBN: 978-3-540-30499-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation