Abstract
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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Brodatz, P.: Textures: a Photographic Album for Artists and Designers. Dover Publications, New York (1966)
Gardner, M.: The Fantastic Combination of John Conways’s New Solitaire Game “Life”. Scientific American 223(4), 120–123 (1970)
Haralick, R.M., Shanmugam, K., Dinstein, I.: Textural features for image classification. IEEE Trans. On System, Man, and Cybernetics, SMC-3(6), 610–621 (1973)
Haralick, R.M.: Statistical and structural approaches to texture. Proceedings of the IEEE 67, 786–804 (1979)
He, D.C., Wang, L.: Texture Unit, Texture Spectrum, and Texture Analysis. IEEE Trans. On Geoscience and Remote Sensing 28(4) (July 1990)
Leguizamón, S.: Description of Terrain Textures by Fractal and Markov Random Fields Techniques. In: Proceedings of the 2nd. International Symposium on HMRS Cartography, Chinese Academy of Sciences, Astronautic Publ. House, P.R. of China, Beijing (1993)
Leguizamón, S.: Characterization of Texture in Remotely Sensed Images by using the Wavelet Transform. In: Proceedings of the IV International Symposium on HMRS Cartography. University of Karlstad, Karlstad (1996)
Preston, K., Duff, M.: Modern Cellular Automata, Theory and Applications. Plenum Press, New York (1984)
Toffoli, T., Margolus, N.: Invertible Cellular Automata: A Review. Physica D 45, 229–253 (1990)
Umarani, C., Ganesan, L., Radhakrishnan, S.: A combined statistical and structural approach for texture representation. Asia J. Inform. Technol. 5, 1434–1440 (2006)
von Neumann, J.: Theory of Self-Reproducing Automata. University of Illinois Press, Champain (1966)
Wolfram, S.: Universality and complexity in cellular automata. Physica D 10 (1984)
Wolfram, S.: A New Kind of Science, http://www.wolframscience.com/nksonline/toc.html (last accessed, March 2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Leguizamón, S., Espínola, M., Ayala, R., Iribarne, L., Menenti, M. (2010). Characterization of Texture in Images by Using a Cellular Automata Approach. In: Lytras, M.D., Ordonez de Pablos, P., Ziderman, A., Roulstone, A., Maurer, H., Imber, J.B. (eds) Organizational, Business, and Technological Aspects of the Knowledge Society. WSKS 2010. Communications in Computer and Information Science, vol 112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16324-1_61
Download citation
DOI: https://doi.org/10.1007/978-3-642-16324-1_61
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16323-4
Online ISBN: 978-3-642-16324-1
eBook Packages: Computer ScienceComputer Science (R0)