• DocumentCode
    1098751
  • Title

    Finding line segments by stick growing

  • Author

    Nelson, Randal C.

  • Author_Institution
    Dept. of Comput. Sci., Rochester Univ., NY, USA
  • Volume
    16
  • Issue
    5
  • fYear
    1994
  • fDate
    5/1/1994 12:00:00 AM
  • Firstpage
    519
  • Lastpage
    523
  • Abstract
    A method is described for extracting lineal features from an image using extended local information to provide robustness and sensitivity. The method utilizes both gradient magnitude and direction information, and incorporates explicit lineal and end-stop terms. These terms are combined nonlinearly to produce an energy landscape in which local minima correspond to lineal features called sticks that can be represented as line segments. A hill climbing (stick-growing) process is used to find these minima. The method is compared to two others, and found to have improved gap-crossing characteristics
  • Keywords
    feature extraction; image segmentation; end-stop terms; extended local information; hill climbing; line segment finding; lineal feature extraction; robustness; sensitivity; stick growing; Data mining; Feature extraction; Geometry; Image edge detection; Image recognition; Pattern recognition; Robot sensing systems; Robotics and automation; Robustness; Shape;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.291445
  • Filename
    291445