• DocumentCode
    3601221
  • Title

    Laplacian Scale-Space Behavior of Planar Curve Corners

  • Author

    Xiaohong Zhang ; Ying Qu ; Dan Yang ; Hongxing Wang ; Kymer, Jeff

  • Author_Institution
    Key Lab. of Dependable Service Comput. in Cyber Phys. Soc., Chongqing, China
  • Volume
    37
  • Issue
    11
  • fYear
    2015
  • Firstpage
    2207
  • Lastpage
    2217
  • Abstract
    Scale-space behavior of corners is important for developing an efficient corner detection algorithm. In this paper, we analyze the scale-space behavior with the Laplacian of Gaussian (LoG) operator on a planar curve which constructs Laplacian Scale Space (LSS). The analytical expression of a Laplacian Scale-Space map (LSS map) is obtained, demonstrating the Laplacian Scale-Space behavior of the planar curve corners, based on a newly defined unified corner model. With this formula, some Laplacian Scale-Space behavior is summarized. Although LSS demonstrates some similarities to Curvature Scale Space (CSS), there are still some differences. First, no new extreme points are generated in the LSS. Second, the behavior of different cases of a corner model is consistent and simple. This makes it easy to trace the corner in a scale space. At last, the behavior of LSS is verified in an experiment on a digital curve.
  • Keywords
    curve fitting; object detection; CSS; LSS map; Laplacian scale-space behavior; Laplacian-of-Gaussian operator; LoG operator; corner detection algorithm; curvature scale space; digital curve; planar curve corners; Analytical models; Cascading style sheets; Detectors; Educational institutions; Laplace equations; Mathematical model; Trajectory; Corner Detection; Corner detection; Laplacian of Gaussian; Planar Curve; Scale Space; planar curve; scale space;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2015.2396074
  • Filename
    7018927