Effective clustering and boundary detection algorithm based on Delaunay triangulation

Liu, Dongquan; Nosovskiy, Gleb V.; Sourina, Olga

doi:10.1016/j.patrec.2008.01.028

Cited by 49 publications

(25 citation statements)

References 22 publications

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“…This algorithm is similar to the proposed algorithm in that it can adaptively discover spatial clusters without the need to set parameters in advance. The implementation class of AUTOCLUST can be obtained from the Web [29]. Table 2.…”

Section: Cpu Time Spent For Clusteringmentioning

confidence: 99%

An Adaptive Sweep-Circle Spatial Clustering Algorithm Based on Gestalt

Zhan

Deng

Zheng³

2017

IJGI

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An adaptive spatial clustering (ASC) algorithm is proposed in this present study, which employs sweep-circle techniques and a dynamic threshold setting based on the Gestalt theory to detect spatial clusters. The proposed algorithm can automatically discover clusters in one pass, rather than through the modification of the initial model (for example, a minimal spanning tree, Delaunay triangulation, or Voronoi diagram). It can quickly identify arbitrarily-shaped clusters while adapting efficiently to non-homogeneous density characteristics of spatial data, without the need for prior knowledge or parameters. The proposed algorithm is also ideal for use in data streaming technology with dynamic characteristics flowing in the form of spatial clustering in large data sets.

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Section: Cpu Time Spent For Clusteringmentioning

confidence: 99%

An Adaptive Sweep-Circle Spatial Clustering Algorithm Based on Gestalt

Zhan

Deng

Zheng³

2017

IJGI

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“…In fact, no particular clustering method has been shown to be superior to its competitors with regards to all the necessary aspects [25,26]. To date, the advantages and disadvantages of various algorithms have been extensively analyzed [26][27][28][29][30][31].An analysis of the classical spatial clustering algorithms is shown in Table 1.…”

Section: Of 23mentioning

confidence: 99%

Section: Cpu Time Spent For Clusteringmentioning

confidence: 99%

An Adaptive Sweep-Circle Spatial Clustering Algorithm Based on Gestalt

Zhan¹,

Deng²,

Zheng³

2017

Preprint

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An adaptive spatial clustering (ASC) algorithm is proposed in this present study, which employs sweep-circle techniques and a dynamic threshold setting based on the Gestalt theory to detect spatial clusters. The proposed algorithm can automatically discover clusters in one pass, rather than through the modification of the initial model (for example, a minimal spanning tree, Delaunay triangulation or Voronoi diagram). It can quickly identify arbitrarily-shaped clusters while adapting efficiently to non-homogeneous density characteristics of spatial data, without the need of prior knowledge or parameters. The proposed algorithm is also ideal for use in data streaming technology with dynamic characteristics flowing in the form of spatial clustering in large data sets.

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“…Delaunay triangulation has been proven to be a powerful tool for capturing spatial proximity in spatial analysis and spatial clustering (Estivill-Castro & Lee, 2002aLee, , 2002bLiu et al, 2008;Lu & Thill, 2008;Tsai, 1993). In this paper, Delaunay triangulation is employed to model the spatial proximity among the spatial points.…”

Section: A New Strategy On Discovering Spatial Clusters In Spatial Damentioning

confidence: 99%