DocumentCode :
2163768
Title :
Detection of compound structures using clustering of statistical and structural features
Author :
Akçay, H. Gökhan ; Aksoy, Selim
Author_Institution :
Bilgisayar Muhendisligi Bolumu, Bilkent Univ., Ankara, Turkey
fYear :
2012
fDate :
18-20 April 2012
Firstpage :
1
Lastpage :
4
Abstract :
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.
Keywords :
edge detection; geophysical image processing; WorldView-2 data; high-level compound structure detection; simple primitive objects; statistical clustering; structural features; structural information; Abstracts; Compounds; Feature extraction; Geoscience and remote sensing; Image segmentation; Spatial resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2012 20th
Conference_Location :
Mugla
Print_ISBN :
978-1-4673-0055-1
Electronic_ISBN :
978-1-4673-0054-4
Type :
conf
DOI :
10.1109/SIU.2012.6204794
Filename :
6204794
Link To Document :
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