• DocumentCode
    2863741
  • Title

    An Image Retrieval Method Based on r/KPSO

  • Author

    Zhang, Xu ; Guo, Bao-Long ; Zhang, Guiyue ; Yan, Yunyi

  • Author_Institution
    Sch. of Electro-Mech. Eng., Xidian Univ., Xi´´an, China
  • fYear
    2011
  • fDate
    16-18 Dec. 2011
  • Firstpage
    69
  • Lastpage
    72
  • Abstract
    Image retrieval is a hot and hard technology in the field of computing science. In this paper, a method named r/KPSO (Particle Swarm Optimization with r- and K-selection) is applied in relevance feedback (RF) of image retrieval. The main idea of r/KPSO is inspired by the r- and K-selection of Ecology. r-selection can be characterized as: quantitative, little parent care, large growth rate and rapid development and K-selection as: qualitative, much parent care, small growth rate and slow development. Based on r/KPSO, we define the positive and negative feedback samples as study principle, and optimize weightings according to user´s retrieval requirement. Experiments show that both the recall and precision are improved effectively.
  • Keywords
    image retrieval; particle swarm optimisation; relevance feedback; K-selection; computing science; image retrieval method; negative feedback; parent care; particle swarm optimization; positive feedback; r-selection; r/KPSO; relevance feedback; user retrieval requirements; Image retrieval; Optimization; Particle swarm optimization; Productivity; Radio frequency; Space exploration; Support vector machines; image retrieval; r- and K-selection; relevance feedback;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovations in Bio-inspired Computing and Applications (IBICA), 2011 Second International Conference on
  • Conference_Location
    Shenzhan
  • Print_ISBN
    978-1-4577-1219-7
  • Type

    conf

  • DOI
    10.1109/IBICA.2011.22
  • Filename
    6118799