Skip to main content

A Novel Artistic Image Generation Technique: Making Relief Effects Through Evolution

  • Conference paper
Advances in Computation and Intelligence (ISICA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4683))

Included in the following conference series:

  • 1388 Accesses

Abstract

The fascinating effect of applying evolutionary algorithms (EAs) to real-world applications consists in its less requirement of knowledge of the applied domain. Many efforts on this idea lead to a new term Nature Inspired Computation, which aims at solving real-world problems with techniques included the nature. Adaptive lossless image compression is one of the most important applications in the field of evolvable hardware(EHW) according to this idea. However, except the adaptive lossless image compression, few extended applications in the field of image processing was reported in the past years. This paper presents a novel evolutionary technique for making relief effects according to the principle of the nature. The proposed method is vary simple and efficient which needs few knowledge about the image precessing, except the common sense that almost all people have. Experimental results show that the proposed method is efficient, and can make quite different effects comparing with conventional method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Eiben, A.E., Smith, J.E.: Introduction to Evolutionary Computing. Springer, Heidelberg (2003)

    MATH  Google Scholar 

  2. Konar, A.: Computational Intelligence: Principles, Techniques and Applications. Springer, Heidelberg (2005)

    MATH  Google Scholar 

  3. Thompson, A., Layzell, P., Zebulum, R.S.: Explorations in Design Space: Unconventional Electronics Design Through Artificial Evolution. IEEE Trans. On Evolutionary Computation 3(3) (September 1999)

    Google Scholar 

  4. Thompson, A., Wasshuber, C.: Evolutionary Design of Single Electron Systems. In: Evolvable Hardware. IEEE Proceedings. The Second NASA/DoD Workshop, July 13-15, 2000, pp. 109–116. IEEE Computer Society Press, Los Alamitos (2000)

    Google Scholar 

  5. Stoica, A., Zebulum, R., Keymeulen, D., et al.: Reconfigurable VLSI Architectures for Evolvable Hardware: from Experimental Field Programable Transistor Arrays to Evolution-oriented Chips. Very Large Scale Integration (VLSI) Systems, IEEE Trans. On 9(1) (February 2001)

    Google Scholar 

  6. Hemmi, H., Hikage, T., Shimahara, K.: AdAM: a hardware evolutionary system. In: IEEE International Conference on Evolutionary Computation, pp. 193–196. IEEE Computer Society Press, Los Alamitos (1997)

    Chapter  Google Scholar 

  7. Yao, X., Higuchi, T.: Promises and challenges of evolvable hardward. IEEE Trans. On Systems, Man, and Cybernetics - Part C: Applications and Reviews 29(1) (February 1999)

    Google Scholar 

  8. Stoica, A., Zebulum, R., Keymeulen, D.: Progress and Challenges in Building Evolvable Devices. In: Evolvable Hardware. IEEE Proceedings. The Third NASA/DoD Workshop, July 12-14, 2001, pp. 33–35. IEEE Computer Society Press, Los Alamitos (2001)

    Google Scholar 

  9. Montana, D., Popp, R., Iyer, S., Vidaver, G.: EvolvaWare: Genetic Programming for Optimal Design of Hardware-Based Algorithms. In: Genetic Programming 1998. Proceedings of the Third Annual Conference, University of Wisconsin, Madison, Wisconsin, USA, July 22-25, 1998, pp. 869–874. Morgan Kaufmann, San Francisco (1998)

    Google Scholar 

  10. Fukunaga, A., Hayworth, K., Stoica, A.: Evolvable Hardware for Spacecraft Autonomy. In: Aerospace Conference, vol. 3, pp. 135–143. IEEE, Los Alamitos (1998)

    Google Scholar 

  11. Stoica, A., Zebulum, R., Keymeulen, D., et al.: Reconfigurable VLSI Architectures for Evolvable Hardware: from Experimental Field Programable Transistor Arrays to Evolution-oriented Chips. Very Large Scale Integration (VLSI) Systems, IEEE Trans. on 9(1) (February 2001)

    Google Scholar 

  12. Higuchi, T., Murakawa, M., Iwata, M., Kajitani, I., Liu, W., Salami, M.: Evolvable hardware at function level. In: IEEE Intemational Conference on Evolutionary Computation, pp. 187–192. IEEE Computer Society Press, Los Alamitos (1997)

    Chapter  Google Scholar 

  13. Highchi, T., Iwata, M., Keymeulen, D., et al.: Real-World Applications of Analog and Digital Evolvable Hardware. IEEE Trans. on Evolutionary Computation 3(3), 220–235 (1999)

    Article  Google Scholar 

  14. Sakanashi, H., Iwata, M., Higuchi, T.: A Lossless Compression Method for Halftone Images using Evolvable Hardware. In: Liu, Y., Tanaka, K., Iwata, M., Higuchi, T., Yasunaga, M. (eds.) ICES 2001. LNCS, vol. 2210, pp. 314–326. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  15. Fukunaga, A., Stechert, A.: Evolving Nonlinear Predictive Models for lossless Image Compression with Genetic Programming. In: Proc.of the Third Annual Genetic Programming Conference, Winsconsin (1998)

    Google Scholar 

  16. He, J., Wang, X., Zhang, M., Wang, J., Fang, Q.: New Research on Scalability of Lossless Image Compression by GP Engine. In: The 2005 NASA/DoD Conference on Evolvable Hardware, The Westin Grand, Washington DC, USA, June 29-July 1, 2005, pp. 160–164 (2005)

    Google Scholar 

  17. He, J., Yao, X., Tang, J.: Towards intrinsic evolvable hardware for predictive lossless image compression. In: Wang, T.-D., Li, X., Chen, S.-H., Wang, X., Abbass, H., Iba, H., Chen, G., Yao, X. (eds.) SEAL 2006. LNCS, vol. 4247, pp. 632–639. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Lishan Kang Yong Liu Sanyou Zeng

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

He, J., Shi, B., Liu, M. (2007). A Novel Artistic Image Generation Technique: Making Relief Effects Through Evolution. In: Kang, L., Liu, Y., Zeng, S. (eds) Advances in Computation and Intelligence. ISICA 2007. Lecture Notes in Computer Science, vol 4683. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74581-5_65

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-74581-5_65

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74580-8

  • Online ISBN: 978-3-540-74581-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics