Detection of compound structures using clustering of statistical and structural features [İstati̇sti̇ksel ve yapisal özni̇teli̇kleri̇n öbeklenmesi̇ i̇le bi̇leşi̇k yapilarin sezi̇mi̇]
2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedings
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Please cite this item using this persistent URLhttp://hdl.handle.net/11693/28194
We describe a new method for detecting compound structures in images by combining the statistical and structural characteristics of simple primitive objects. A graph is constructed by assigning the primitive objects to its vertices, and connecting potentially related objects using edges. Statistical information that is modeled using spectral, shape, and position data of individual objects as well as the structural information that is modeled in terms of spatial alignments of neighboring object groups are also encoded in this graph. Experiments using WorldView-2 data show that hierarchical clustering of the graph vertices can discover high-level compound structures that cannot be obtained using traditional techniques. © 2012 IEEE.
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