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A Novel Shape Descriptor Based on Interrelation Quadruplet

  • Dongil Han
  • Bum-Jae You
  • Sang-Rok Oh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3211)

Abstract

In this paper, we propose a new shape descriptor, which represents the 2-D shape information by using the concept of interrelation quadruplet. For this purpose, the polygonal approximation of 2-D shape is applied first. The line segments can be extracted from the polygonal shapes and the definition of interrelation quadruplet between ling segments is introduced. The properties of interrelation quadruplet that is invariant to translation, rotation and scaling of a pair of line segments is described. Several useful properties of the interrelation quadruplet are also derived in relation to efficient partial shape recognition. The shape recognition using the interrelation quadruplet requires only small space of storage and is shown to be computationally simple and efficient.

Keywords

Line Segment Shape Descriptor Shape Information Zernike Moment Polygonal Shape 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Dongil Han
    • 1
  • Bum-Jae You
    • 2
  • Sang-Rok Oh
    • 2
  1. 1.Department of Computer EngineeringSejong UniversitySeoulKorea
  2. 2.Intelligent Robotics Research CenterKorea Institute of Science and TechnologySeoulKorea

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