• DocumentCode
    2914887
  • Title

    Detecting local features in complex images: A combination of Hough transform and moment-based approximations

  • Author

    Sluzek, Andrzej

  • Author_Institution
    Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore
  • fYear
    2008
  • fDate
    17-20 Dec. 2008
  • Firstpage
    1323
  • Lastpage
    1328
  • Abstract
    The paper presents fundamentals and preliminary results of a technique for defining, building and positioning novel local feature. The features are created by approximating the content of a scanning circular window by a collection of predefined patterns. Although basics of the technique have been discussed in previous papers, the major modification is the introduction of Hough transform as a part of the algorithm. By applying a modified Hough transform to the contents of scanning windows, approximations can be build more reliably (the algorithm is not sensitive to so-called ldquovisual intrusionsrdquo) more accurately (localization of features is more precise) and at lower computational costs (a part of complex mathematics in previously used moment-based approximations can be avoided).
  • Keywords
    Hough transforms; approximation theory; image matching; object detection; Hough transforms; complex image; local feature detection; moment-based approximation; scanning window; Computer vision; Detectors; Image analysis; Image matching; Image retrieval; Information retrieval; Machine vision; Object detection; Robotics and automation; Shape; Hough transform; Image matching; keypoints; local features; moments;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Automation, Robotics and Vision, 2008. ICARCV 2008. 10th International Conference on
  • Conference_Location
    Hanoi
  • Print_ISBN
    978-1-4244-2286-9
  • Electronic_ISBN
    978-1-4244-2287-6
  • Type

    conf

  • DOI
    10.1109/ICARCV.2008.4795713
  • Filename
    4795713