• DocumentCode
    3500925
  • Title

    Face Recognition Based on the Phase Spectrum of Local Normalized Image

  • Author

    Olivares-Mercado, Jesus ; Hotta, Kazuhiro ; Takahashi, Haruhisa ; Perez-Meana, Hector ; Sanchez-Perez, Gabriel

  • fYear
    2008
  • fDate
    27-31 Oct. 2008
  • Firstpage
    123
  • Lastpage
    127
  • Abstract
    This paper proposes a robust faces recognition method based on the phase spectrum features of the local normalized image. The principal components analysis (PCA) and the support vector machine (SVM) are used in the classification stage. We evaluate how the proposed method is robust to illumination, occlusion and expressions using "AR face database", which includes the face images of 109 subjects (60 males and 49 females) under illumination changes, expression changes and partial occlusion. The proposed method provides results with a correct recognition rate more than 95.5%.
  • Keywords
    face recognition; feature extraction; image classification; principal component analysis; support vector machines; visual databases; PCA; SVM; face recognition; local normalized image; partial occlusion; phase spectrum; phase spectrum features; principal components analysis; support vector machine; Biometrics; Character recognition; Data mining; Face recognition; Image recognition; Lighting; Principal component analysis; Robustness; Support vector machine classification; Support vector machines; Face Recognition; Local Normalized Image; PCA; Phase Spectrum; SVM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence, 2008. MICAI '08. Seventh Mexican International Conference on
  • Conference_Location
    Atizapan de Zaragoza
  • Print_ISBN
    978-0-7695-3441-1
  • Type

    conf

  • DOI
    10.1109/MICAI.2008.46
  • Filename
    4682453