Skip to main content

On the Evaluation of Images Complexity: A Fuzzy Approach

  • Conference paper
Fuzzy Logic and Applications (WILF 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3849))

Included in the following conference series:

Abstract

The inherently multidimensional problem of evaluating the complexity of an image is of a certain relevance in both computer science and cognitive psychology. Computer scientists usually analyze spatial dimensions, to deal with automatic vision problems, such as feature-extraction. Psychologists seem more interested in the temporal dimension of complexity, to explore attentional models. Is it possible, by merging both approaches, to define an more general index of visual complexity? We have defined a fuzzy mathematical model of visual complexity, using a specific entropy function; results obtained by applying this model to pictorial images have a strong correlation with ones from an experiment with human subjects based on variation of subjective temporal estimations associated with changes in visual attentional load, which is also described herein.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Cardaci, M.: The Mental Clock Model - Studies on the Structure of Time. Physics to Psycho(patho)logy. In: Buccheri, L., Di Gesù, V. (eds.). Kluwer Academic/Plenum Publishers, New York (2000)

    Google Scholar 

  2. Ornstein, R.E.: The Psychology of Consciousness. Freeman and Company, San Francisco (1972)

    Google Scholar 

  3. Di Gesù, V., Roy, S.: Fuzzy measures for image distance. Advances in Fuzzy Systems and Intelligent Technologies. In: Masulli, F., Parenti, R., Pasi, G. (eds.). Shaker Publishing (NL), Ithaca (2000)

    Google Scholar 

  4. Marr, D., Hildreth, E.: Theory of Edge Detection. Proc. R. Soc. Lond. B. 207, 187–217 (1980)

    Article  Google Scholar 

  5. Petrou, M.: The Differentiating Filter Approach to Edge Detection. Advances in Electronics and Electron Physics 88, 297–345 (1994)

    Google Scholar 

  6. Di Gesù, V., Valenti, C.: Symmetry operators in computer vision. Vistas in Astronomy, Pergamon 40(4), 461–468 (1996)

    Article  Google Scholar 

  7. De Luca, A., Termini, S.: Information and Control, vol. 20, p. 301 (1972)

    Google Scholar 

  8. Oliva, A., Mack, M.L., Shrestha, M., Peeper, A.: Identifying the perceptual dimensions of visual complexity of scenes. In: Proc. of the 27th Annual Meeting of the Cognitive Science Society, Chicago (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Cardaci, M., Di Gesù, V., Petrou, M., Tabacchi, M.E. (2006). On the Evaluation of Images Complexity: A Fuzzy Approach. In: Bloch, I., Petrosino, A., Tettamanzi, A.G.B. (eds) Fuzzy Logic and Applications. WILF 2005. Lecture Notes in Computer Science(), vol 3849. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11676935_38

Download citation

  • DOI: https://doi.org/10.1007/11676935_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-32529-1

  • Online ISBN: 978-3-540-32530-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics