A cluster detection algorithm based on percolation theory

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Abstract

We describe a novel algorithm for the detection of clusters of points embedded in background noise in the plane. The algorithm is based on the percolation phenomena found in random graphs obtained from a planar Poisson process. We estimate the time complexity of the algorithm and its expected performance.

Original languageEnglish (US)
Pages (from-to)199-202
Number of pages4
JournalPattern Recognition Letters
Volume12
Issue number4
DOIs
StatePublished - Apr 1991
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence
  • Signal Processing
  • Computer Vision and Pattern Recognition

Keywords

  • Cluster
  • Poisson process
  • percolation
  • random graph

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