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Evolving Textures from High Level Descriptions: Gray with an Accent Color

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Applications of Evolutionary Computation (EvoApplications 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6625))

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Abstract

This paper describes a prototype evolutionary texture synthesis tool meant to assist a designer or artist by automatically discovering many candidate textures that fit a given stylistic description. The textures used here are small color images, created by procedural texture synthesis. This prototype uses a single stylistic description: a textured gray image with a small amount of color accent. A hand-written prototype fitness function rates how well an image meets this description. Genetic programming uses the fitness function to evolve programs written in a texture synthesis language. A tool like this can automatically generate a catalog of variations on the given theme. A designer could then scan through these to pick out those that seem aesthetically interesting. Their procedural “genetic” representation would allow them to be further adjusted by interactive evolution. It also allows re-rendering them at arbitrary resolutions and provides a way to store them in a highly compressed form allowing lossless reconstruction.

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Author information

Authors and Affiliations

  1. US R&D, Sony Computer Entertainment, USA

    Craig Reynolds

Authors
  1. Craig Reynolds
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Statistics, University of Strathclyde, 16 Richmond Street, G1 1XQ, Glasgow, UK

    Cecilia Di Chio

  2. School of Business, University College Dublin, 4, Belfield, Dublin, UK

    Anthony Brabazon

  3. Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), Galleria 2, 6928, Manno-Lugano, Switzerland

    Gianni A. Di Caro

  4. Institute of Computer Science, University of Bremen, 28359, Bremen, Germany

    Rolf Drechsler

  5. Next Generation Intelligent Networks Research Center (nexGIN RC), National University of Computer & Emerging Sciences (FAST-NU), Islamabad, Pakistan

    Muddassar Farooq

  6. Department of Information Systems, Johannes Gutenberg-Universität, 55099, Mainz, Germany

    Jörn Grahl

  7. Mathematics and Computer Science Depatment, University of Richmond, 23173, Richmond, VA, USA

    Gary Greenfield

  8. ICD - OSI, University of Technology of Troyes, 12, Rue Marie Curie, BP 2060, 10010, Troyes, France

    Christian Prins

  9. Facultad de Informatica, Universidade de A Coruña, 15071, Coruña, CP, Spain

    Juan Romero

  10. Dipartimento di Automatica e Informatica, Politecnico di Torino, Italy

    Giovanni Squillero

  11. Consiglio Nazionale delle Ricerche (CNR), Istituto di Calcolo e Reti ad Alte Prestazioni (ICAR), Via P. Castellino 111, 80131, Naples, Italy

    Ernesto Tarantino

  12. Dipartimento di Tecnologie dell’Informazione, Università degli Studi di Milano, Via Bramante 65, 26013, Crema (CR), Italy

    Andrea G. B. Tettamanzi

  13. School of Computing, Edinburgh Napier University, 10 Clinton Road, EH10 5DT, Edinburgh, UK

    Neil Urquhart

  14. Computer Engineering Department, Istanbul Technical University, Room Nr. 3302, Maslak, 34469, Istanbul, Turkey

    A. Şima Uyar

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© 2011 Springer-Verlag Berlin Heidelberg

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Reynolds, C. (2011). Evolving Textures from High Level Descriptions: Gray with an Accent Color. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2011. Lecture Notes in Computer Science, vol 6625. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20520-0_39

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  • DOI: https://doi.org/10.1007/978-3-642-20520-0_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20519-4

  • Online ISBN: 978-3-642-20520-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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