Author:
Eelco den Heijer
Affiliation:
Vrije Universiteit, Netherlands
Keyword(s):
Evolutionary Art, Aesthetic Measures, Computational Aesthetics, Symmetry, Compositional Balance.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Evolutionary Art and Design
;
Evolutionary Computing
;
Genetic Algorithms
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Soft Computing
Abstract:
In this paper we present our research into the unsupervised evolution of aesthetically pleasing images using measures for symmetry, compositional balance and liveliness. We evolve images without human aesthetic evaluation, and use measures for symmetry, compositional balance and liveliness as fitness functions. Our symmetry measure calculates the difference in intensity of opposing pixels around one or more axes. Our measure of compositional balance calculates the similarity between two parts of an image using a color image distance function. Using the latter measure, we are able to evolve images that show a notion of ‘balance’ but are not necessarily symmetrical. Our measure for liveliness uses the entropy of the intensity of the pixels of the image. We performed a number of experiments in which we evolved aesthetically pleasing images using the aesthetic measures, in order to evaluate the effect of each fitness function on the resulting images. We also performed an experiment using
a combination of aesthetic measures using a multi-objective evolutionary algorithm (NSGA-II).
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