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

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

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

Access to Document

10.1016/0167-8655(91)90032-H

Cite this

@article{27df44b6a72f4c5b802c6b69fe2b5847,

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.",

author = "Craig Gotsman",

year = "1991",

month = jan,

day = "1",

doi = "10.1016/0167-8655(91)90032-H",

language = "English (US)",

volume = "12",

pages = "199--202",

journal = "Pattern Recognition Letters",

issn = "0167-8655",

publisher = "Elsevier",

number = "4",

}

TY - JOUR

T1 - A cluster detection algorithm based on percolation theory

AU - Gotsman, Craig

PY - 1991/1/1

Y1 - 1991/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0025953123&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0025953123&partnerID=8YFLogxK

U2 - 10.1016/0167-8655(91)90032-H

DO - 10.1016/0167-8655(91)90032-H

M3 - Article

AN - SCOPUS:0025953123

SN - 0167-8655

VL - 12

SP - 199

EP - 202

JO - Pattern Recognition Letters

JF - Pattern Recognition Letters

IS - 4

ER -

A cluster detection algorithm based on percolation theory

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Cite this