A complex network-based approach for texture analysis

Authors:
André Ricardo Backes;Dalcimar Casanova;Odemir Martinez Bruno
Affiliations:
Faculdade de Computação, Universidade Federal de Uberlândia, Uberlândia, MG, Brasil;Instituto de Física de São Carlos, São Carlos, Brasil;Instituto de Física de São Carlos, São Carlos, Brasil
Venue:
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
Year:
2010

Citing 5
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Abstract

In this paper, we propose a novel texture analysis method using the complex network theory. It was investigated how a texture image can be effectively represented, characterized and analyzed in terms of a complex network. The propose uses degree measurements in a dynamic evolution network to compose a set of feasible shape descriptors. Results show that the method is very robust and it presents a very excellent texture discrimination for all considered classes.