IDEAS home Printed from https://ideas.repec.org/a/igg/jitwe0/v11y2016i3p1-14.html
   My bibliography  Save this article

Image Mosaicing Using Binary Edge Detection Algorithm in a Cloud-Computing Environment

Author

Listed:
  • Abdullah Alamareen

    (Jordan University of Science and Technology, Irbid, Jordan)

  • Omar Al-Jarrah

    (Jordan University of Science and Technology, Irbid, Jordan)

  • Inad A. Aljarrah

    (Computer Engineering Department, Jordan University of Science and Technology, Irbid, Jordan)

Abstract

Image Mosaicing is an image processing technique that arises from the need of having a more realistic view of the real world wider than the view captured by the lenses of the available cameras. In this paper, a sequence of images will be mosaiced using binary edge detection algorithm in a cloud-computing environment to improve processing speed and accuracy. The authors have used Platform as a Service (PaaS) to provide a number of nodes in the cloud to run the computational intensive image processing and stitching algorithms. This increased the processing speed as most of image processing algorithms deal with every single pixel in the image. Message Passing Interface (MPI) is used for message passing among the compute-nodes in the cloud and a MapReduce technique is used for image distribution and collection, where the root node is used as reducer and the others as mappers. After applying the algorithm on different sequence of images and different machines on JUST cloud, the authors have achieved high mosaicing accuracy, and the execution time has been improved when comparing it with sequential execution on the images.

Suggested Citation

  • Abdullah Alamareen & Omar Al-Jarrah & Inad A. Aljarrah, 2016. "Image Mosaicing Using Binary Edge Detection Algorithm in a Cloud-Computing Environment," International Journal of Information Technology and Web Engineering (IJITWE), IGI Global, vol. 11(3), pages 1-14, July.
    • Handle: RePEc:igg:jitwe0:v:11:y:2016:i:3:p:1-14
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJITWE.2016070101
    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:jitwe0:v:11:y:2016:i:3:p:1-14. 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.