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Proceedings Paper

Complex networks: application for texture classification
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Paper Abstract

This article describes a new method and approch of texture characterization. Using complex network representation of an image, classical and derived (hierarchical) measurements, we presente how to have good performance in texture classification. Image is represented by a complex networks: one pixel as a node. Node degree and clustering coefficient, using with traditional and extended hierarchical measurements, are used to characterize "organisation" of textures.

Paper Details

Date Published: 29 May 2007
PDF: 7 pages
Proc. SPIE 6356, Eighth International Conference on Quality Control by Artificial Vision, 63561E (29 May 2007); doi: 10.1117/12.737170
Show Author Affiliations
T. Chalumeau, Le2i, Univ. de Bourgogne (France)
Univ. de Sao Paulo (Brazil)
L. da F. Costa, Univ. de Sao Paulo (Brazil)
O. Laligant, Le2i, Univ. de Bourgogne (France)
F. Meriaudeau, Le2i, Univ. de Bourgogne (France)

Published in SPIE Proceedings Vol. 6356:
Eighth International Conference on Quality Control by Artificial Vision
David Fofi; Fabrice Meriaudeau, Editor(s)

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