Paper Info
Title
Linear belts mining from spatial database with mathematical morphological operators
Abstract
In order to mine one typical non-sphere cluster, the linear belts in a spatial database, a mathematical morphological operator based method is proposed in this paper. The method can be divided into two basic steps: firstly, the most suitable re-segmenting scale is found by our clustering algorithm MSCMO which is based on mathematical morphological scale space; secondly, the segmented result at this scale is re-segmented to obtain the final linear belts. This method is a robust mining method to semi-linear clusters and noises, which is validated by the successful extraction of seismic belts.
Year
DOI
Venue
2005
10.1007/11527503_91
ADMA
Keywords
Field
DocType
seismic belt,robust mining method,clustering algorithm mscmo,basic step,suitable re-segmenting scale,linear belts mining,mathematical morphological operator,mathematical morphological scale space,spatial database,segmented result,linear belt,final linear belt,scale space
Data mining,Cluster (physics),Mathematical morphology,Segmentation,Computer science,Scale space,Information extraction,Operator (computer programming),Cluster analysis,Spatial database
Conference
Volume
ISSN
ISBN
3584
0302-9743
3-540-27894-X
Citations 
PageRank 
References 
0
0.34
5
Authors
3
Name
Order
Citations
PageRank
Min Wang1162.53
Jian-Cheng Luo29920.75
Chenghu Zhou326440.93