• DocumentCode
    2709874
  • Title

    Face identification for people image with general background using vector phase field

  • Author

    Shu, Qingyu ; Hattori, Tetsuo ; Izumi, Tetsuya ; Kitajima, Hiroyuki ; Yamasaki, Toshinori

  • Author_Institution
    Grad. Sch. of Eng., Kagawa Univ., Kagawa
  • fYear
    2008
  • fDate
    21-24 April 2008
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper proposes an automatic identification method of an acquaintancepsilas face from people image with general background. In this method, we assume that a face in a given image approximately equals to be an Affine transformed (rotated, enlarged/reduced and translated) pattern of registered original one, and that the face pattern is also perturbed by a lighting variation and noise. The recognition method deals with a vector phase field (VPF) that is a normalized gradient vector field obtained from input grey level image. The VPF shows a kind of feature representation for face pattern, while it gives an insensitive feature to lighting variations on the input image. In addition to the representation, we use a region-weighted similarity over the VPF in order to improve the identification accuracy. This paper also presents the experimental results of the proposed method, and illustrates its effectiveness by comparing with non region weighted case.
  • Keywords
    face recognition; gradient methods; image registration; image representation; affine transformed pattern; automatic acquaintance face identification method; face pattern feature representation; general background; input grey level image; normalized gradient vector field; people image; region-weighted similarity; registered original face; vector phase field; Color; Eyes; Face detection; Face recognition; Image recognition; Karhunen-Loeve transforms; Noise reduction; Nose; Pixel; Terminology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Technology, 2008. ICIT 2008. IEEE International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-1705-6
  • Electronic_ISBN
    978-1-4244-1706-3
  • Type

    conf

  • DOI
    10.1109/ICIT.2008.4608673
  • Filename
    4608673