IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/8217250.html
   My bibliography  Save this article

A Novel Image Retrieval Based on a Combination of Local and Global Histograms of Visual Words

Author

Listed:
  • Zahid Mehmood
  • Syed Muhammad Anwar
  • Nouman Ali
  • Hafiz Adnan Habib
  • Muhammad Rashid

Abstract

Content-based image retrieval (CBIR) provides a sustainable solution to retrieve similar images from an image archive. In the last few years, the Bag-of-Visual-Words (BoVW) model gained attention and significantly improved the performance of image retrieval. In the standard BoVW model, an image is represented as an orderless global histogram of visual words by ignoring the spatial layout. The spatial layout of an image carries significant information that can enhance the performance of CBIR. In this paper, we are presenting a novel image representation that is based on a combination of local and global histograms of visual words. The global histogram of visual words is constructed over the whole image, while the local histogram of visual words is constructed over the local rectangular region of the image. The local histogram contains the spatial information about the salient objects. Extensive experiments and comparisons conducted on Corel-A, Caltech-256, and Ground Truth image datasets demonstrate that the proposed image representation increases the performance of image retrieval.

Suggested Citation

  • Zahid Mehmood & Syed Muhammad Anwar & Nouman Ali & Hafiz Adnan Habib & Muhammad Rashid, 2016. "A Novel Image Retrieval Based on a Combination of Local and Global Histograms of Visual Words," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-12, August.
    • Handle: RePEc:hin:jnlmpe:8217250
    DOI: 10.1155/2016/8217250
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2016/8217250.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2016/8217250.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2016/8217250?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:8217250. 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.