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Ontological Imaging [O-I] with Case Studies

  • Nikolaos E. Myridis
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 184)

Summary

In this paper we inaugurate the shaping of a new Imaging field, that of Ontological Imaging, in order to diversify the families of images which are dedicated to convey semantic content. The images of this area can be characterized as ontological, in distinction to images characterized by the term ’artistic’ (in a broader sense). The space of applications regarding Ontological Imaging seems to be inexhaustible. Thus we cite herein two broad areas of applications, that is: (a) imaging of mathematical entities and (b) sub-visual imaging of processes. We give also two significant case studies, regarding the previous areas: (a) imaging of real numbers and (b) imaging of mathematical constants.

Keywords

Semantic Content Decimal Digit Mathematical Entity Communication Challenge Aesthetic Sensibility 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Finch, S.: Mathematical Constants. Cambridge University Press, N.Y. (2005)Google Scholar
  2. 2.
    Gomez-Perez, A., Fernandez-Lopez, M., Corcho, O.: Ontological Engineering. Springer, Berlin (2004)Google Scholar
  3. 3.
    Kozaki, K., Hirota, T., Mizoguchi, R.: Understanding an Ontology through Divergent Exploration. In: Antoniou, G., Grobelnik, M., Simperl, E., Parsia, B., Plexousakis, D., De Leenheer, P., Pan, J. (eds.) ESWC 2011, Part I. LNCS, vol. 6643, pp. 305–320. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  4. 4.
    Krellenstein, M.: Unsolvable Problems, Visual Imagery and Explanatory Satisfaction. J. Mind and Behav. 16, 235–253 (1995)Google Scholar
  5. 5.
    Myridis, N.E., Chamzas, C.: Sampling on Concentric Circles. IEEE Trans. Med. Imag. 17(2), 294–299 (1998)CrossRefGoogle Scholar
  6. 6.
    Myridis, N.E.: The Image Whole and the Image Eye Diagram [IED]. In: Choraś, R.S. (ed.) Image Processing and Communications Challenges 3. AISC, vol. 102, pp. 123–129. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  7. 7.
    Sinclair, N., Pimm, D., Higginson, W. (eds.): Mathematics and the Aesthetic. Springer, N.York (2006)zbMATHGoogle Scholar
  8. 8.
    Terzidis, K.: Algorithmic Architecture. Architectural Press (2006)Google Scholar
  9. 9.
    Triantaphyllou, E., Felici, G. (eds.): Data Mining & Knowledge Discovery. Springer, Berlin (2006)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Aristotle University of ThessalonikiThessalonikiGreece

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