Linear belts mining from spatial database with mathematical morphological operators

Authors:
Min Wang;Jiancheng Luo;Chenghu Zhou
Affiliations:
Nanjing Normal University, Nanjing, China;State Key Laboratory of Resources & Environment Information System, Institute of Geographical Sciences and Natural Resources Research, Beijing, China;State Key Laboratory of Resources & Environment Information System, Institute of Geographical Sciences and Natural Resources Research, Beijing, China
Venue:
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Year:
2005

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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.