• DocumentCode
    467665
  • Title

    Face Recognition Research Based on Anti-Symmetrical Wavelet and Eigenface

  • Author

    Yin, Qian ; Yuan, Zhi-Yong ; Kong, Ying ; Guo, Ping

  • Author_Institution
    Beijing Normal Univ., Beijing
  • Volume
    1
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    366
  • Lastpage
    371
  • Abstract
    In this paper, a new human face recognition method based on anti-symmetrical biorthogonal wavelet transformation (ASBWT) and eigenface was proposed. First the anti-symmetrical biorthogonal wavelet is chosen to degrade the face image dimension, meanwhile complete the process of face location and segmentation; And then human face is reverted through the face space of eigenface, the traditional average human face is replaced in the within-class scatter matrix. This within-class scatter matrix is used to calculate within-class and between-class distance proportion as a rule function, calculate the twice eigenface through discrete Karhunen-Loeve transform (DKLT), and use singular value decomposition (SVD) method to calculate the eigenvector. Finally we compute the weights and classify the face images. The results show that the proposed method has higher recognition rate and more robust than the traditional eigenface analysis method.
  • Keywords
    discrete wavelet transforms; eigenvalues and eigenfunctions; face recognition; singular value decomposition; antisymmetrical biorthogonal wavelet transformation; discrete Karhunen-Loeve transform; eigenface analysis method; eigenvector; human face recognition; singular value decomposition; within-class scatter matrix; Degradation; Face recognition; Fourier transforms; Humans; Image coding; Matrices; Matrix decomposition; Robustness; Scattering; Wavelet analysis; Anti-symmetrical biorthogonal wavelet; Eigenface; Face recognition; SVD;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370171
  • Filename
    4370171