• DocumentCode
    714535
  • Title

    Geometrical shape recognition based on CDF extreme points analysis

  • Author

    Ozturk, Mehmet

  • Author_Institution
    Elektrik - Elektron. Muhendisligi Bolumu, Karadeniz Teknik Univ., Trabzon, Turkey
  • fYear
    2015
  • fDate
    16-19 May 2015
  • Firstpage
    1449
  • Lastpage
    1452
  • Abstract
    Automated shape recognition is a common problem which have been faced in computer vision applications. The feature(s) used to classify shapes should be chosen well for an accurate and fast way. Centroid distance function curve is a widely used feature in this field because of its quick and easy calculation properties. This study which is aimed to classify 2D convex geometric shapes based on the analysis of extreme points of the curve is proposed. The proposed method is robust to translation, rotation and scale of the objects.
  • Keywords
    computer vision; geometry; shape recognition; 2D convex geometric shapes; CDF; automated shape recognition; centroid distance function curve; computer vision; extreme points analysis; geometrical shape recognition; Algorithm design and analysis; Computer vision; Computers; Pattern recognition; Robustness; Shape; Transforms; centroid distance function; computer vision; extreme point analysis; geometrical shape recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2015 23th
  • Conference_Location
    Malatya
  • Type

    conf

  • DOI
    10.1109/SIU.2015.7130116
  • Filename
    7130116