IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-030-41862-5_125.html
   My bibliography  Save this book chapter

Content Based Image Retrieval: Using Edge Detection Method

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

Author

Listed:
  • P. John Bosco

    (Pondicherry University, Banking Technology)

  • S. K. V. Jayakumar

    (Pondicherry University, Banking Technology)

Abstract

Content-Based Image Retrieval task is still a challenging problem, Edge Detection method is an important role in image processing and big challenge task in feature extraction which can be fundamental problem in image analysis. Edge detection methods are a strong feature for characterizing an image. In this approach to make robust techniques for extracting edge pixels by edge feature detection, we propose a Multiple Edge Detection (MED) frame work for image re-ranking. In this approach multi-edge detection techniques like Roberts, Sobel, Prewitt, Canny, LoG (Laplacian of Gaussian) etc., of an image which are followed by combined edge feature using gray level as well as shape information of edges map. Our aim is to maximize the image retrieval combined edge detection methods which promote more relevant re-ranking image results. The experimental results proved the efficiency of the proposed method.

Suggested Citation

  • P. John Bosco & S. K. V. Jayakumar, 2020. "Content Based Image Retrieval: Using Edge Detection Method," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 1239-1247, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_125
    DOI: 10.1007/978-3-030-41862-5_125
    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_125. 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.