IDEAS home Printed from https://ideas.repec.org/a/igg/jmdem0/v8y2017i2p22-32.html
   My bibliography  Save this article

Static Signature Verification Based on Texture Analysis Using Support Vector Machine

Author

Listed:
  • Subhash Chandra

    (Indian Institute of Technology, Department of Computer Science and Engineering, Indian Institute of Technology, Dhanbad, India)

  • Sushila Maheshkar

    (Indian Institute of Technology, Department of Computer Science and Engineering, Indian Institute of Technology, Dhanbad, India)

Abstract

Off-line hand written signature verification performs at the global level of image. It processes the gray level information in the image using statistical texture features. The textures and co-occurrence matrix are analyzed for features extraction. A first order histogram is also processed to reduce different writing ink pens used by signers. Samples of signature are trained with SVM model where random and skilled forgeries have been used for testing. Experimental results are performed on two databases: MCYT-75 and GPDS Synthetic Signature Corpus.

Suggested Citation

  • Subhash Chandra & Sushila Maheshkar, 2017. "Static Signature Verification Based on Texture Analysis Using Support Vector Machine," International Journal of Multimedia Data Engineering and Management (IJMDEM), IGI Global, vol. 8(2), pages 22-32, April.
    • Handle: RePEc:igg:jmdem0:v:8:y:2017:i:2:p:22-32
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJMDEM.2017040103
    Download Restriction: no
    ---><---

    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:igg:jmdem0:v:8:y:2017:i:2:p:22-32. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.