IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/641510.html
   My bibliography  Save this article

A Fuzzy Kernel Maximum Margin Criterion for Image Feature Extraction

Author

Listed:
  • Shibin Xuan

Abstract

Based on kernel principal component analysis, fuzzy set theory, and maximum margin criterion, a novel image feature extraction and recognition method, called fuzzy kernel maximum margin criterion (FKMMC), is proposed. In the proposed method, two new fuzzy scatter matrixes are redefined. The new fuzzy scatter matrix can reflect fully the relation between fuzzy membership degree and the offset of the training sample to subclass center. Besides, a concise reliable computational method of the fuzzy between-class scatter matrix is provided. Experimental results on four face databases (AR, extended Yale B, GTFD, and FERET) demonstrate that the proposed method outperforms other methods.

Suggested Citation

  • Shibin Xuan, 2015. "A Fuzzy Kernel Maximum Margin Criterion for Image Feature Extraction," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-13, April.
    • Handle: RePEc:hin:jnlmpe:641510
    DOI: 10.1155/2015/641510
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2015/641510.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2015/641510.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2015/641510?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:641510. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.