• DocumentCode
    2660192
  • Title

    Facial features for identification

  • Author

    Kouzani, A.Z. ; Nahavandi, S.

  • Author_Institution
    Sch. of Eng. & Technol., Deakin Univ., Geelong, Vic., Australia
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1372
  • Abstract
    A person identification system is presented in this paper. The system exploits the localised self-similarity in face images in order to develop an identification method. The identification method is insensitive to partial image variations that are due to translation, rotation or scale. The performance of the system is evaluated by studying the results of its application to ensembles of face images
  • Keywords
    biometrics (access control); face recognition; feature extraction; fractals; identification; invariance; software performance evaluation; face image ensembles; facial features; localised self-similarity; partial image variations; performance evaluation; person identification system; rotation invariance; scale invariance; translation invariance; Australia; Facial features; Hidden Markov models; Image motion analysis; Independent component analysis; Optical devices; Partitioning algorithms; Pixel; Shape; Vents;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 2000 IEEE International Conference on
  • Conference_Location
    Nashville, TN
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-6583-6
  • Type

    conf

  • DOI
    10.1109/ICSMC.2000.886045
  • Filename
    886045