• DocumentCode
    3176641
  • Title

    Face Recognition Based on Modified Modular Principal Component Analysis

  • Author

    Zhang, Xingfu

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin, China
  • fYear
    2009
  • fDate
    21-22 Dec. 2009
  • Firstpage
    67
  • Lastpage
    72
  • Abstract
    The technology of face recognition has been widely applied to many fields such as identity authentication. A New Improvement for Face Recognition Using MMPCA is presented in this paper. The proposed algorithm when compared with conventional modular PCA algorithm is different in the computation of image mean value and the recognition process. Comparison of the two algorithms in different face databases proves that the proposed algorithm is more effective and robust than conventional modular PCA algorithm under the large variations in lighting direction and facial expression. The authors also point out that 2DPCA is a special case of improved algorithm, no matter in the process of dimension reduction or recognition.
  • Keywords
    face recognition; principal component analysis; MMPCA; dimension reduction; face recognition; facial expression; identity authentication; image mean value; modified modular principal component analysis; modular PCA algorithm; Algorithm design and analysis; Computer science; Data preprocessing; Educational institutions; Face recognition; Image recognition; Internet; Machine learning algorithms; Principal component analysis; Robustness; Face Recognition; Modular Principal Component Analysis; Principal Component Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Internet Computing for Science and Engineering (ICICSE), 2009 Fourth International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4244-6754-9
  • Type

    conf

  • DOI
    10.1109/ICICSE.2009.29
  • Filename
    5521628