abstract = "The automatic synthesis of aesthetically pleasing
images is investigated. Genetic programming with
multiobjective fitness evaluation is used to evolve
procedural texture formulae. With multi-objective
fitness testing, candidate textures are evaluated
according to multiple criteria. Each criteria
designates a dimension of a multi-dimensional fitness
space. The main feature test uses Ralph's model of
aesthetics. This aesthetic model is based on empirical
analyses of ne art, in which analysed art work exhibits
bell curve distributions of colour gradients.
Subjectively speaking, this bell-curve gradient
measurement tends to favour images that have harmonious
and balanced visual characteristics. Another feature
test is colour histogram scoring. This test permits
some control of the color composition, by matching a
candidate texture's color composition with the colour
histogram of a target image. This target image may be a
digital image of another artwork. We found that the use
of the bell curve model often resulted in images that
were harmonious and easy-on-the-eyes. Without the use
of the model, generated images were often too chaotic
or boring. Although our approach does not guarantee
aesthetically pleasing results, it does increase",
notes = "WCCI 2006 - A joint meeting of the IEEE, the EPS, and
the IEE.