Fuzzy mathematical approach to pattern recognition
Fuzzy mathematical approach to pattern recognition
A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
An introduction to Kolmogorov complexity and its applications (2nd ed.)
An introduction to Kolmogorov complexity and its applications (2nd ed.)
Visual Attention Mechanisms
Some new fuzzy entropy formulas
Fuzzy Sets and Systems
Scale Adaptive Complexity Measure of 2D Shapes
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
IEEE Transactions on Fuzzy Systems
An information-theoretic framework for image complexity
Computational Aesthetics'05 Proceedings of the First Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
Estimating watermarking capacity in gray scale images based on image complexity
EURASIP Journal on Advances in Signal Processing
A knowledge driven approach to aerospace condition monitoring
Knowledge-Based Systems
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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.