• DocumentCode
    3446082
  • Title

    Face recognition using fuzzy rough set and support vector machine

  • Author

    Wang, Shi-Yi ; Tao Liang

  • Author_Institution
    MOE Key Lab. of Intell. Comput. & Signal Process., Anhui Univ., Hefei, China
  • Volume
    2
  • fYear
    2010
  • fDate
    29-31 Oct. 2010
  • Firstpage
    777
  • Lastpage
    779
  • Abstract
    This paper proposes a method of face recognition using the support vector machine (SVM) based on the fuzzy rough set theory (FRST). Firstly, features from human face images are extracted by combining the 2-D wavelet decomposition technique with the grayscale integral projection technique. And then, the attribute reduction algorithm based on FRST is applied in face recognition. The reduction algorithm based on FRST can eliminate the redundant features of sample dataset and reduce the space dimension of the sample data. The proposed method avoids losing of information caused by dispersing before original rough set attribute reduction. Experimental results show that it can improve the classification accuracy in face recognition as compared with the method using the original rough set.
  • Keywords
    face recognition; feature extraction; fuzzy set theory; rough set theory; support vector machines; wavelet transforms; attribute reduction algorithm; face feature extraction; face recognition; fuzzy rough set; grayscale integral projection technique; support vector machine; wavelet decomposition technique; Face; attribute reduction; fuzzy rough set; rough set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4244-6582-8
  • Type

    conf

  • DOI
    10.1109/ICICISYS.2010.5658621
  • Filename
    5658621