• DocumentCode
    615420
  • Title

    An advanced BPNN face recognition based on curvelet transform and 2DPCA

  • Author

    Ye Jihua ; Hu Dan ; Xia Guomiao ; Chen Yahui

  • Author_Institution
    Comput. & Inf. Eng. Coll., Jiangxi Normal Univ., Nanchang, China
  • fYear
    2013
  • fDate
    26-28 April 2013
  • Firstpage
    1019
  • Lastpage
    1022
  • Abstract
    The paper proposed an advanced face recognition method of BPNN based on Curvelet transform and 2DPCA to increase the face recognition rate.. Firstly, we used Curvelet transform to process the face images, after that we got higher dimension feature of face images, then used 2DPCA to reduce the dimension, finally we got some feature vectors, which could represent the face images. We used ORL face database to conduct the experiment, some of the feature vectors to train the BPNN classifier, the others to test. we repeatedly made some of the less important feature vectors value replaced by zeros, and made the recognition result depend on big probability event . We obtained a better result In this way compared with traditional BPNN face recognition, this method can not only improve the face recognition rate, but also reduce the recognition time.
  • Keywords
    backpropagation; curvelet transforms; face recognition; feature extraction; image classification; image representation; neural nets; principal component analysis; probability; visual databases; 2DPCA; BPNN classifier training; BPNN face recognition; ORL face database; backpropagation neural network; curvelet transform; dimension reduction; face image dimension feature; face image processing; face images representation; face recognition rate; feature vectors; probability event; recognition time reduction; Face; Face recognition; Indexes; 2DPCA; BPNN; Curvelet; Face recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science & Education (ICCSE), 2013 8th International Conference on
  • Conference_Location
    Colombo
  • Print_ISBN
    978-1-4673-4464-7
  • Type

    conf

  • DOI
    10.1109/ICCSE.2013.6554063
  • Filename
    6554063