Texture analysis and classification: A complex network-based approach

  • Authors:
  • André Ricardo Backes;Dalcimar Casanova;Odemir Martinez Bruno

  • Affiliations:
  • Universidade Federal de Uberlíndia, Faculdade de Computação, Brazil;Universidade de São Paulo, Instituto de Física de São Carlos, Brazil;Universidade de São Paulo, Instituto de Física de São Carlos, Brazil

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2013

Quantified Score

Hi-index 0.07

Visualization

Abstract

In this paper, we propose a novel texture analysis method using the complex network theory. We investigated how a texture image can be effectively represented, characterized and analyzed in terms of a complex network. The proposed approach uses degree measurements to compose a set of texture descriptors. The results show that the method is very robust, and it presents a excellent texture discrimination for all considered classes, overcoming traditional texture methods.