• Login
    View Item 
    •   DSpace Home
    • Institute's contributions
    • Scholarly literature
    • View Item
    •   DSpace Home
    • Institute's contributions
    • Scholarly literature
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    A review on SIFT and SURF for underwater image feature detection and matching

    Thumbnail
    Date
    2019
    Author
    Ansari, S.
    Metadata
    Show full item record
    Abstract
    Fast and robust image recognition and matching is an important task in the underwater domain. Autonomous Underwater Vehicles (AUV) use images for detecting and recognising object or scene of interest. Interest points are extracted from images that are captured by the camera on the AUV. In this paper, feature detectors SIFT and SURF are investigated as applicable to the underwater environment. They are reviewed and compared in terms of robustness, accuracy, and speed with the aim of identifying a method which is computationally-efficient in finding good corresponding points between two underwater images
    URI
    http://drs.nio.org/drs/handle/2264/8098
    Collections
    • Scholarly literature [9127]

    DSpace software copyright © 2002-2016  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    Atmire NV
     

     

    Browse

    All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    DSpace software copyright © 2002-2016  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    Atmire NV