Advertisement

Survey on Simplified Olfactory Bionic Model to Generate Texture Images

  • Zhang Jin
  • Deng Yang
  • Li Yong-jun
  • Wang Ying
  • Wang Ru-long
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7664)

Abstract

In order to improve performance of artificial neural networks (ANNs) generating texture images, simplified olfactory bionic model (SOBM) to generate texture images is proposed by Zhang in 2008. In this paper, a series of related researches are surveyed. SOBM is introduced from three aspects and texture images with different style are surveyed. Otherwise, SOBM are analyzed synthetically from qualitative and quantitive aspects according to different factors effecting texture images.

Keywords

Bionic model Olfactory neural system Texture image Image expressing space Gray-level co-occurrence matrix (GLCM) 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Sreedevi, P., Wen-Liang, H., Shawmin, L.: An Examplar-based Approach for Texture Compaction Synthesis and Retrieval. IEEE Transactions on Image Processing 19(5), 1307–1318 (2010)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Wei, L.Y., Levoy, M.: Fast Texture Synthesis Using Tree-structured Vector Quantization. In: SigGraph 2000, pp. 479–488 (2000)Google Scholar
  3. 3.
    Jiang, J.L., Xue, F., Zheng, J.Y., Huang, Z.: A Fast Algorithm for Solid Texture Generation from 2D Sample. Journal of Computer-aided Design & Computer Graphics 23(8), 1311–1318 (2011)Google Scholar
  4. 4.
    Wu, X.P., Zhou, H.Q., Feng, H.Q.: The Texture Image Generation Based on Neural Network. Journal of Image and Graphics 5(6), 484–488 (2000)Google Scholar
  5. 5.
    Zheng, L.Y., Tian, K., Wang, K.J.: The Method of Texture Image Generation Based on Chaotic Mapping. Journal of Image and Graphics 7(10), 1009–1011 (2002)Google Scholar
  6. 6.
    Bi, X.J., Li, W.X.: A New Method for Texture Image Synthesis. Techniques of Automation and Applications 24(1), 22–24 (2005)Google Scholar
  7. 7.
    Zhang, J., Li, G., Freeman, W.J.: Algorithm for Texture Image Generation Based on a Bionic Model of Olfactory Neural Networks. Journal of Image and Graphics 13(5), 977–983 (2008)Google Scholar
  8. 8.
    Zhang, J., Fang, C., Zhao, L.J., Liljenstrom, H.: On Color Texture Generating Based on Simplified KIII Model. In: Proc. of Eighth IEEE/ACIS International Conference on Computer and Information Science, pp. 93–96 (2009)Google Scholar
  9. 9.
    Zhang, J., Zhu, S.W., Wang, R.L., Li, G., Walter, F.J.: A New Method to Generate Color Texture Images Based on HSV and Olfactory System Bionic Model. In: Proc. of 2009 International Joint Conference on Neural Networks, pp. 1446–1449 (2009)Google Scholar
  10. 10.
    Fang, C., Zhang, J., Zhu, S., Li, G., Wang, R.: Analysis of Texture Images Generated by Olfactory System Bionic Model. In: Zeng, Z., Wang, J. (eds.) Advances in Neural Network Research and Applications. LNEE, vol. 67, pp. 453–459. Springer, Heidelberg (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Zhang Jin
    • 1
  • Deng Yang
    • 1
  • Li Yong-jun
    • 1
  • Wang Ying
    • 2
  • Wang Ru-long
    • 1
  1. 1.College of Information Science and EngineeringHunan UniversityChangshaChina
  2. 2.School of Humanities, Information Technology and ManagementHunan Univerisyt of Chinese MedicineChangshaChina

Personalised recommendations