A cluster detection algorithm based on percolation theory

Craig Gotsman

doi:10.1016/0167-8655(91)90032-H

A cluster detection algorithm based on percolation theory

Craig Gotsman

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

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 language	English (US)
Pages (from-to)	199-202
Number of pages	4
Journal	Pattern Recognition Letters
Volume	12
Issue number	4
DOIs	https://doi.org/10.1016/0167-8655(91)90032-H
State	Published - Jan 1 1991
Externally published	Yes

All Science Journal Classification (ASJC) codes

Computer Vision and Pattern Recognition
Signal Processing
Electrical and Electronic Engineering

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10.1016/0167-8655(91)90032-H

Cite this

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title = "A cluster detection algorithm based on percolation theory",

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.",

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A cluster detection algorithm based on percolation theory

Abstract

All Science Journal Classification (ASJC) codes

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