Detection of compound structures using clustering of statistical and structural features
Author
Akçay, H. Gökhan
Aksoy, Selim
Date
2012Source Title
2012 20th Signal Processing and Communications Applications Conference (SIU)
Publisher
IEEE
Language
Turkish
Type
Conference PaperItem Usage Stats
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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. © 2012 IEEE.
Keywords
Compound structuresGraph vertex
Hier-archical clustering
Individual objects
Object groups
Position data
Spatial alignment
Statistical information
Structural characteristics
Structural feature
Structural information
Traditional techniques
Signal processing
Graph theory
Permalink
http://hdl.handle.net/11693/28194Published Version (Please cite this version)
http://dx.doi.org/10.1109/SIU.2012.6204794Collections
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