• DocumentCode
    2709969
  • Title

    A new method to generate color texture images based on HSV and olfactory system bionic model

  • Author

    Jin, Zhang ; Shang-wu, Zhu ; Wang Ru-long ; Guang, Li ; Freeman, Walter J.

  • Author_Institution
    Sch. of Software, Hunan Univ., Changsha, China
  • fYear
    2009
  • fDate
    14-19 June 2009
  • Firstpage
    1446
  • Lastpage
    1449
  • Abstract
    A new method to generate color texture images is proposed in this paper, which derived from our previous works to generate the gray texture. The method is based on the olfactory system bionic model to generate the gray texture. The model architecture mimics that of mammal olfactory neural system. Period function is used as the activity function of nodes in the model to realize the periodic repetition of texture. Chaotic mapping is used to adjust the model parameters to assure the model being in non-convergence state. The previous input is introduced as the noise to simulate the background noise of neural system. One color image is used as seed image. In HSV space, the Hue (H), saturation (S) and value (V) of each pixel is used as the model input and the model output is composed as the H, S and V of corresponding pixel in generated texture. Experimental results show that the proposed method can generate many beautiful color textures, whose textures are different from the original texture.
  • Keywords
    biocybernetics; chaos; image colour analysis; image texture; neural nets; HSV space; chaotic mapping; color texture images; gray texture image; mammal olfactory neural system; olfactory system bionic model; period function; seed image; Background noise; Chaos; Colored noise; Educational institutions; Image generation; Nerve fibers; Neural networks; Olfactory; Solid modeling; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2009. IJCNN 2009. International Joint Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-3548-7
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2009.5178807
  • Filename
    5178807