### Abstract

Original language | English |
---|---|

Pages (from-to) | 1474-1484 |

Number of pages | 11 |

Journal | Fuzzy Sets and Systems |

Volume | 160 |

Publication status | Published - 2009 |

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### All Science Journal Classification (ASJC) codes

- Logic
- Artificial Intelligence

### Cite this

*Fuzzy Sets and Systems*,

*160*, 1474-1484.

**A fuzzy approach to the evaluation of image complexity.** / Tabacchi, Marco; Di Gesu', Vito; Cardaci, Maurizio; Petrou, Maria.

Research output: Contribution to journal › Article

*Fuzzy Sets and Systems*, vol. 160, pp. 1474-1484.

}

TY - JOUR

T1 - A fuzzy approach to the evaluation of image complexity

AU - Tabacchi, Marco

AU - Di Gesu', Vito

AU - Cardaci, Maurizio

AU - Petrou, Maria

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

KW - Complexity

KW - Fuzzy entropy

KW - Fuzzy sets

KW - Image analysis

KW - Internal clock

KW - Mental clock

UR - http://hdl.handle.net/10447/40549

M3 - Article

VL - 160

SP - 1474

EP - 1484

JO - Fuzzy Sets and Systems

JF - Fuzzy Sets and Systems

SN - 0165-0114

ER -