Los Angeles, CA
March 31, 2009 to April 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.638
Spatial Mining differs from regular data mining in parallel with the difference in spatial and non-spatial data. The attributes of a spatial object is influenced by the attributes of the spatial object and moreover by the spatial location. In this paper, we propose a new algorithm for spatial mining by applying an image extraction method on hierarchical Quad tree spatial data structure. Homogeneity of the grid is the entropy measure which decides the further subdivision of the quadrant. Finally, the algorithm proceeds by applying low level image extraction on domain dense nodes of the quad tree.
Spatial data mining, clustering, image information content, quad tree
Unnikrishnan A., Paulose Jacob, "Information Content Extraction on Quad Trees for Active Spatial Image Clustering", CSIE, 2009, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, pp. 306-310, doi:10.1109/CSIE.2009.638