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Evolving Pop Art Using Scalable Vector Graphics

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7247)

Abstract

In this paper we present our findings of our continued investigation into the use of Scalable Vector Graphics as a genotype representation in evolutionary art. In previous work we investigated the feasibility of SVG as a genetic representation for evolutionary art, and found that the representation was very flexible, but that the potential visual output was somewhat limited by the simplicity of our genetic operators. In this paper we extend on this work, and introduce various new, more expressive genetic operators for SVG. We show that SVG is a flexible and powerful representation for evolutionary art, and that the potential visual output is only limited by the design of the genetic operators. With the genetic operators that we describe in this paper, we are able to evolve art that is visually similar to screen printing art and pop art.

Keywords

  • Genetic Operator
  • Image Collection
  • Colour Scheme
  • Symbolic Expression
  • Raster Image

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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den Heijer, E., Eiben, A.E. (2012). Evolving Pop Art Using Scalable Vector Graphics. In: Machado, P., Romero, J., Carballal, A. (eds) Evolutionary and Biologically Inspired Music, Sound, Art and Design. EvoMUSART 2012. Lecture Notes in Computer Science, vol 7247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29142-5_5

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  • DOI: https://doi.org/10.1007/978-3-642-29142-5_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29141-8

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