• DocumentCode
    3247070
  • Title

    Face Recognition by PCA Technique

  • Author

    Patil, A.M. ; Kolhe, Satish R. ; Patil, Pradeep M.

  • Author_Institution
    Dept. of Electron. & Telecommun. Eng., J.T.M. Coll. of Eng., Faizpur, India
  • fYear
    2009
  • fDate
    16-18 Dec. 2009
  • Firstpage
    192
  • Lastpage
    195
  • Abstract
    Face recognition is one of the most active research areas in computer vision and pattern recognition with practical applications. This work proposes an appearance based eigenface technique. PCA is used in extracting the relevant information in human faces. In this method the eigenvectors of the set of training images are calculated which define the face space. Face images are projected on to the face space which encodes the variation among known face images. These encoded variations are used for recognition. Experiments are carried on IndianFace Database; the obtained recognition rate is 92.30%. The same training set is tested with nonface database.
  • Keywords
    eigenvalues and eigenfunctions; face recognition; principal component analysis; PCA technique; computer vision; eigenface technique; eigenvectors; face recognition; pattern recognition; Application software; Computer vision; Data mining; Face detection; Face recognition; Humans; Image databases; Pattern recognition; Principal component analysis; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Trends in Engineering and Technology (ICETET), 2009 2nd International Conference on
  • Conference_Location
    Nagpur
  • Print_ISBN
    978-1-4244-5250-7
  • Electronic_ISBN
    978-0-7695-3884-6
  • Type

    conf

  • DOI
    10.1109/ICETET.2009.99
  • Filename
    5395405