Characterization of Texture in Images by Using a Cellular Automata Approach

  • Saturnino Leguizamón
  • Moisés Espínola
  • Rosa Ayala
  • Luis Iribarne
  • Massimo Menenti
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 112)


Spatial patterns in an image that shows a visual perception of roughness or softness of the surface is known as the texture of the image. Most of the analysis and description of texture found in the literature is based on statistical or structural properties of this attribute [2]. The field of cellular automata (CA), which has been developed mainly to model the dynamical behavior of systems, is based on the behavior or arrangements of pixel values and their neighborhood which, according to some rules behaves in different manners [2, 8]. In this paper, within the frame of structural approach, a novel method based on the properties of linear cellular automata is proposed to characterize different sort of textures. To this purpose, it is assumed that a binary version of the image under study was generated by a cellular automata technique. By using this model a number of textural primitives are found which allows the production of a characterizing image. In order to verify the feasibility of the proposed method, texture images generated by CA techniques as well as natural images has been used.


Cellular Automaton Cellular Automaton Markov Random Field Cellular Automaton Model Decimal Number 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Saturnino Leguizamón
    • 1
  • Moisés Espínola
    • 2
  • Rosa Ayala
    • 2
  • Luis Iribarne
    • 2
  • Massimo Menenti
    • 3
  1. 1.Regional Faculty of MendozaNational Technnological UniversityArgentina
  2. 2.Applied Computing GroupUniversity of AlmeríaSpain
  3. 3.Aerospace Engineering Optical and Laser Remote SensingTU DelftThe Netherlands

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