• DocumentCode
    3200303
  • Title

    Biometrics security and experiments on face recognition algorithms

  • Author

    Dandashi, Amal ; Karam, Walid

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Balamand, Koura, Lebanon
  • fYear
    2012
  • fDate
    11-13 July 2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Biometrics security analysis and performance evaluation of the following Face Recognition Algorithms is performed: Principal Components Analysis (PCA), Linear Discriminant Analysis (LDA) and Bayesian Intrapersonal/Extrapersonal Classifier (BIC), using the BANCA database. Software tools retrieve and preprocess images from sequential records within the BANCA database for algorithm evaluation. Then a verification environment over the set of images to be tested is developed, the above algorithms are invoked over the verification set, and verification parameters are collected. Results proved PCA performed most accurately and effectively with regards to security concerns, with an average recognition rate of 93%, while LDA and BIC lagged behind with recognition rates ranging from 80%-83%.
  • Keywords
    Bayes methods; biometrics (access control); face recognition; image classification; principal component analysis; security of data; software tools; BANCA database; BIC; Bayesian intrapersonal/extrapersonal classifier; LDA; PCA; biometrics security analysis; face recognition algorithm; linear discriminant analysis; performance evaluation; principal components analysis; software tool; verification environment; verification parameter; verification set; Algorithm design and analysis; Biometrics; Databases; Face recognition; Principal component analysis; Testing; Training; BANCA Database; algorithms; biometrics security; face recognition; performance evaluation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Security and Defence Applications (CISDA), 2012 IEEE Symposium on
  • Conference_Location
    Ottawa, ON
  • Print_ISBN
    978-1-4673-1416-9
  • Type

    conf

  • DOI
    10.1109/CISDA.2012.6291532
  • Filename
    6291532