The Visual Computer

, Volume 28, Issue 1, pp 35–45 | Cite as

Automatic and interactive evolution of vector graphics images with genetic algorithms

  • Steven Bergen
  • Brian J. Ross
Original Article


Vector graphics are popular in illustration and graphic design. Images are composed of discrete geometric shapes, such as circles, squares, and lines. The generation of vector images by evolutionary computation techniques, however, has been given little attention. JNetic is an implementation of a comprehensive evolutionary vector graphics tool. Vector primitives available range from simple geometric shapes (circles, polygons) to spline-based paint strokes. JNetic supports automatic and user-guided evolution, chromosome editing, and high-detail masks. Automatic evolution involves measuring the pixel-by-pixel colour distance between a candidate and target image. Masks can be painted over areas of the target image, which help reproduce the high-detail features within those areas. By creative selection of primitives and colour schemes, stylized interpretations of target images are produced. The system has been successfully used by the authors as a creative tool.


Genetic algorithm Vector graphics Evolutionary art 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bachelier, G.: Embedding of pixel-based evolutionary algorithms in my global art process. In: Romero, J., Machado, P. (eds.) The Art of Artificial Evolution. Springer, Berlin (2008) Google Scholar
  2. 2.
    Barile, P., Ciesielski, V., Trist, K., Berry, M.: Animated drawings rendered by genetic programming. In: Proc. GECCO 2009. ACM Press, New York (2009) Google Scholar
  3. 3.
    Bentley, P., Corne, D.W.: Creative Evolutionary Systems. Morgan Kaufmann, San Mateo (2002) Google Scholar
  4. 4.
    Bergen, S., Ross, B.J.: Evolutionary art using summed multi-objective ranks. In: Riolo, R., McConaghy, T., Vladislavleva, E. (eds.) Genetic Programming—Theory and Practice VIII. Springer, Berlin (2010) Google Scholar
  5. 5.
    Boudreau, T., Jesse, G., Greene, S., Woehr, J., Spurlin, V.: NetBeans: The Definitive Guide. O’Reilly, Farnham (2002) Google Scholar
  6. 6.
    Buckley, R.: Parallelohedra and uniform colour quanitzation. In: Paeth, A.W. (ed.) Graphics Gems, pp. 65–71. Academic Press, New York (1995) Google Scholar
  7. 7.
    Burton, A.R., Vladimirova, T.: Generation of musical sequences with genetic techniques. Comput. Music J. 23(4), 59–73 (1999) CrossRefGoogle Scholar
  8. 8.
    Dawkins, R.: The Blind Watchmaker. WW Norton, New York (1996) Google Scholar
  9. 9.
    Dorin, A.: Aesthetic fitness and artificial evolution for the selection of imagery from the mythical infinite library. In: Advances in Artificial Life—Proc. 6th European Conference on Artificial Life, pp. 659–668. Springer, Berlin (2001) Google Scholar
  10. 10.
    Dorin, A.: Artificial life, death, and epidemics in evolutionary, generative, electronic art. In: Applications of Evolutionary Computing: EvoWorkShops 2005, pp. 448–457. Springer, Berlin (2005) CrossRefGoogle Scholar
  11. 11.
    Ebert, D.S., Musgrave, F.K., Peachey, D., Perlin, K., Worley, S.: Texturing and Modeling: A Procedural Approach. Academic Press, New York (1994) Google Scholar
  12. 12.
    Eiben, A.E.: Evolutionary reproduction of Dutch masters: The Mondriaan and Escher evolvers. In: Romero, J., Machado, P. (eds.) The Art of Artificial Evolution. Springer, Berlin (2008) Google Scholar
  13. 13.
    Elliot, J., Eckstein, R., Loy, M., Wood, D., Cole, B.: Java Swing (2e). O’Reilly, Farnham (2002) Google Scholar
  14. 14.
    Frowd, C.D., Hancock, P.J.B.: Evolving human faces. In: Romero, J., Machado, P. (eds.) The Art of Artificial Evolution. Springer, Berlin (2008) Google Scholar
  15. 15.
    Gervautz, M., Purgathofer, W.: A simple method for colour quantization: octree quantization. In: Glassner, A.S. (ed.) Graphics Gems, pp. 287–293. Academic Press, New York (1990) Google Scholar
  16. 16.
    Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison Wesley, Reading (1989) zbMATHGoogle Scholar
  17. 17.
    Graf, J., Banzhaf, W.: Interactive evolution of images. In: Proc. Intl. Conf. on Evolutionary Programming, pp. 53–65 (1995) Google Scholar
  18. 18.
    Greenfield, G.: Evolving expressions and art by choice. Leonardo 33(2), 93–99 (2000) CrossRefGoogle Scholar
  19. 19.
    Greenfield, G.: Evolving aesthetic images using multiobjective optimization. In: Proc. CEC 2003, pp. 1903–1909 (2003) Google Scholar
  20. 20.
    Holland, J.H.: Adaptation in Natural and Artificial Systems. MIT Press, Cambridge (1992) Google Scholar
  21. 21.
    Ibrahim, A.E.M.: GenShade: an evolutionary approach to automatic and interactive procedural texture generation. PhD thesis, Texas A&M University (December 1998) Google Scholar
  22. 22.
    IllustratorWorld. (2011). Last accessed Jan 26, 2011
  23. 23.
    Jackson, H.: Toward a symbiotic coevolutionary approach to architecture. In: Bentley, P.J., Corne, D.W. (eds.) Creative Evolutionary Systems, pp. 299–313. Morgan Kaufmann, San Mateo (2002) CrossRefGoogle Scholar
  24. 24.
    Klawonn, F.: Introduction to Computer Graphics: Using Java 2D and 3D. Springer, Berlin (2008) CrossRefGoogle Scholar
  25. 25.
    Lewis, M.: Aesthetic evolutionary design with data flow networks. In: Proc. Generative Art 2000 (2000) Google Scholar
  26. 26.
    Machado, P., Cardoso, A.: Computing aesthetics. In: Proc. XIVth Brazilian Symposium on AI, pp. 239–249. Springer, Berlin (1998) Google Scholar
  27. 27.
    Neufeld, C., Ross, B., Ralph, W.: The evolution of artistic filters. In: Romero, J., Machado, P. (eds.) The Art of Artificial Evolution. Springer, Berlin (2008) Google Scholar
  28. 28.
    O’Neill, M., Swafford, J.M., McDermott, J., Byrne, J., Brabazon, A., Shotton, E., McNally, C., Hemberg, M.: Shape grammars and grammatical evolution for evolutionary design. In: Proc. GECCO’09, pp. 1035–1042. ACM, New York (2009) Google Scholar
  29. 29.
    Romero, J., Machado, P.: The Art of Artificial Evolution. Springer, Berlin (2008) CrossRefGoogle Scholar
  30. 30.
    Rooke, S.: Eons of genetically evolved algorithmic images. In: Bentley, P.J., Corne, D.W. (eds.) Creative Evolutionary Systems, pp. 330–365. Morgan Kaufmann, San Mateo (2002) Google Scholar
  31. 31.
    Ross, B.J., Ralph, W., Zong, H.: Evolutionary image synthesis using a model of aesthetics. In: CEC 2006, July 2006 Google Scholar
  32. 32.
    Sims, K.: Interactive evolution of equations for procedural models. Vis. Comput. 9, 466–476 (1993) CrossRefGoogle Scholar
  33. 33.
    Sun, H., Liang, L., Wen, F., Shum, H.-Y.: Image vectorization using optimized gradient meshes. ACM Trans. Graph. 26(3) (2007) Google Scholar
  34. 34.
    Svangard, N., Nordin, P.: Automated aesthetic selection of evolutionary art by distance based classification of genomes and phenomes using the universal similarity metric. In: Applications of Evolutionary Computing: EvoWorkshops 2004. LNCS, vol. 3005, pp. 447–456. Springer, Berlin (2004) CrossRefGoogle Scholar
  35. 35.
    Swaminarayan, S., Prasad, L.: Rapid automated polygonal image decomposition. In: Proc. 35th Applied Imagery and Pattern Recognition Workshop, pp. 28–33 (2006) Google Scholar
  36. 36.
    Todd, S., Latham, W.: Evolutionary Art and Computers. Academic Press, New York (1992) zbMATHGoogle Scholar
  37. 37.
    Weller, C.: Generation of vector-based graphics from existing bitmap images by means of the genetic algorithm (2002). Last accessed April 28, 2009 Google Scholar
  38. 38.
    Whitelaw, M.: Breeding aesthetic objects: Art and artificial evolution. In: Bentley, P., Corne, D.W. (eds.) Creative Evolutionary Systems, pp. 129–145. Morgan Kaufmann, San Mateo (2002) CrossRefGoogle Scholar
  39. 39.
    Wiens, A.L., Ross, B.J.: Gentropy: Evolutionary 2D texture generation. Comput. Graph. J. 26(1), 75–88 (2002) CrossRefGoogle Scholar
  40. 40.
    Wijesinghe, G., Sah, S., Ciesielski, V.: Grid vs arbitrary placement for generating animated photomosaics. In: CEC 2008, pp. 2739–2745 (2008) Google Scholar
  41. 41.
    Wilkens, S.: Rendering non-photorealistic images by means of a genetic algorithm. Unpublished student project (2005) Google Scholar
  42. 42.
    Xia, T., Liao, B., Yu, Y.: Patch-based image vectorization with automatic curvilinear feature alignment. ACM Trans. Graph. 28(5) (2009) Google Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  1. 1.Department of Computer ScienceBrock UniversitySt. CatharinesCanada

Personalised recommendations