Elsevier

Fuzzy Sets and Systems

Volume 160, Issue 10, 16 May 2009, Pages 1474-1484
Fuzzy Sets and Systems

A fuzzy approach to the evaluation of image complexity

https://doi.org/10.1016/j.fss.2008.11.017Get rights and content

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 in order to deal with automatic vision problems, such as feature extraction. Psychologists seem more interested in the temporal dimension of complexity, as a means to explore attentional models. Is it possible to define, by merging both approaches, a more general index of visual complexity? The aim of this paper is the definition of objective measures of image complexity that fits with the so named perceived time. Towards the end we have defined a fuzzy mathematical model of visual complexity, based on fuzzy measures of entropy; the results obtained by applying this model to a set of pictorial images present a strong correlation with the outcomes of an experiment with human subjects, based on variation of subjective temporal estimations associated with changes in visual attentional load, which is also described herein.

References (32)

  • A. Klinger, N.A. Salingaros, Complexity and visual images, Technical Report...
  • F. Masulli et al.

    Ambiguity and structural information in the perception of reversible figures

    Perception and Psychophysics

    (1989)
  • F. Masulli, M. Riani, E. Simonotto, F. Vannucci, Boltzmann distributions and neural networks: models of unbalanced...
  • E. Leeuwenberg, H. Buffart, An outline of coding theory, in: H. Geisler, H. Buffart, E. Leeuwenberg, V. Sarris (Eds.),...
  • J. Rigau, M. Feixas, M. Sbert, An Information-Theoretic Framework for Image Complexity, Computational Aesthetics in...
  • I. Mario, M. Chacon, D. Alma, S. Corral, Image complexity measure: a human criterion free approach, in: Proc. NAFIPS...
  • Cited by (63)

    • Characterising and dissecting human perception of scene complexity

      2023, Cognition
      Citation Excerpt :

      As computing systems became more powerful, and the field of information science evolved, so too have definitions of complexity. One computational technique often applied as an analogue of visual complexity involves the calculation of the Shannon entropy of the image (Cardaci et al., 2009; Yu & Winkler, 2013), under the hypothesis that more complex images have a greater level of entropy (or disorganisation), and simpler images contain more redundant information (and hence, lower entropy). Entropy-based measures appear to be one method of operationalising visual clutter (Rosenholtz et al., 2007), as the more cluttered the image, the more disorganised the image, hence the greater entropy.

    View all citing articles on Scopus
    View full text