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Shape decomposition for graph representation

  • Cai Luyuan*
  • , Zhao Meng
  • , Liu Shang
  • , Mao Xiaoyan
  • , Bai Xiao
  • *Corresponding author for this work
  • China University of Geosciences, Wuhan
  • Beihang University
  • CAS - Beijing Institute of Control Engineering

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

The problem of shape analysis has played an important role in the area of image analysis, computer vision and pattern recognition. In this paper, we present a new method for shape decomposition. The proposed method is based on a refined morphological shape decomposition process.We provide two more analysis for morphological shape decomposition. The first step is scale invariant analysis. We use a scale hierarchy structure to find the invariant parts in all different scale level. The second step is noise deletion. We use graph energy analysis to delete the parts which have minor contribution to the average graph energy. Our methods can solve two problems for morphological decomposition - scale invariant and noise. The refined decomposed shape can then be used to construct a graph structure. We experiment our method on shape analysis.

Original languageEnglish
Title of host publicationSoftware Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2010
EditorsRoger Lee
Pages1-10
Number of pages10
DOIs
StatePublished - 2010

Publication series

NameStudies in Computational Intelligence
Volume295
ISSN (Print)1860-949X

Keywords

  • Graph spectra
  • Image shape analysis
  • Shape recognition

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