Paper
29 May 2007 Complex networks: application for texture classification
Author Affiliations +
Proceedings Volume 6356, Eighth International Conference on Quality Control by Artificial Vision; 63561E (2007) https://doi.org/10.1117/12.737170
Event: Eighth International Conference on Quality Control by Artificial Vision, 2007, Le Creusot, France
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
T. Chalumeau, L. da F. Costa, O. Laligant, and F. Meriaudeau "Complex networks: application for texture classification", Proc. SPIE 6356, Eighth International Conference on Quality Control by Artificial Vision, 63561E (29 May 2007); https://doi.org/10.1117/12.737170
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Cited by 1 scholarly publication.
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KEYWORDS
Image classification

Matrices

Binary data

Gaussian filters

Image processing

Network security

Transform theory

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