Advertisement

Face Recognition Using a Neural Network Simulating Olfactory Systems

  • Guang Li
  • Jin Zhang
  • You Wang
  • Walter J. Freeman
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)

Abstract

A novel chaotic neural network K-set has been constructed based in research on biological olfactory systems. This non-convergent neural network simulates the capacities of biological brains for signal processing in pattern recognition. Its accuracy and efficiency are demonstrated in this report on an application to human face recognition, with comparisons of performance with conventional pattern recognition algorithms.

Keywords

Feature Vector Face Recognition Face Image Wavelet Packet Olfactory System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Freeman, W.J., Kozma, R.: Biocomplexity: Adaptive Behavior in Complex Stochastic Dynamic Systems. Biosystems 59, 109–123 (2001)CrossRefGoogle Scholar
  2. 2.
    Li, G., Lou, Z., Wang, L., Li, X., Freeman, W.J.: Application of Chaotic Neural Model Based on Olfactory System on Pattern Recognitions. In: Wang, L., Chen, K., Ong, Y. S. (eds.) ICNC 2005. LNCS, vol. 3610, pp. 378–381. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  3. 3.
    Pan, Z., Adams, R., Bolouri, H.: Dimensionality Reduction of Face Images Using Discrete Cosine Transforms for Recognition. IEEE Conference on Computer Vision and Pattern Recognition (2000)Google Scholar
  4. 4.
    Samaria, F.: Face Recognition Using Hidden Markov Models, PhD Thesis, Cambridge University (1994)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Guang Li
    • 1
  • Jin Zhang
    • 2
    • 3
  • You Wang
    • 2
  • Walter J. Freeman
    • 4
  1. 1.National Laboratory of Industrial Control TechnologyZhejiang UniversityHangzhouChina
  2. 2.Department of Biomedical EngineeringZhejiang UniversityHangzhouChina
  3. 3.Software CollegeHuman UniversityChangshaChina
  4. 4.Division of NeurobiologyUniversity of California at BerkeleyBerkeleyUSA

Personalised recommendations