IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-030-41862-5_175.html
   My bibliography  Save this book chapter

Real Time Facial Recognition System

In: New Trends in Computational Vision and Bio-inspired Computing

Author

Listed:
  • Ashwini

    (SRM IST, Department of CSE)

  • Vijay Balaji

    (SRM IST, Department of CSE)

  • Srivarshini Srinivasan

    (SRM IST, Department of CSE)

  • Kavya Monisha

    (SRM IST, Department of CSE)

Abstract

The main aim of the proposed work is to develop a three module face detection and recognition system. This system is mainly centralized on distinguishing the full frontal face present in the encompassed digital image or video. Our system assists the user to detect faces appearing in a video/webcam. In this process, the image fed as output by the user, is verified by referencing it with a federated database. The database assimilates a good deal of digital images from all the authorized users, who can pass through the system. The metadata is trained for effectuating the system’s purpose. This trained data is then used for recognizing the face present on the webcam or the image. If an image corresponds to the fed image, then the suitable data will displayed. This system is implemented with the help of openCV library. This library extends a FaceRecogniser class, which contains algorithms for performing the recognition process. Our system uses the local binary patterns histogram for achieving the result.

Suggested Citation

  • Ashwini & Vijay Balaji & Srivarshini Srinivasan & Kavya Monisha, 2020. "Real Time Facial Recognition System," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 1721-1726, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_175
    DOI: 10.1007/978-3-030-41862-5_175
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:spr:sprchp:978-3-030-41862-5_175. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.