• DocumentCode
    1962698
  • Title

    Research and application of Content-Based adaptive image retrieval technology

  • Author

    Liu, Chunyu ; Zhang, Zhiliang

  • Author_Institution
    Dalian Neusoft Inst. of Inf., Dalian
  • fYear
    2009
  • fDate
    11-13 May 2009
  • Firstpage
    68
  • Lastpage
    72
  • Abstract
    In this paper, a new image retrieving method is proposed, which integrates color features, and integrates color histogram, relevance feedback, the partition color and the genetic algorithms. First, by analyzing images´ color histogram, dasiaexample imagespsila which have the same global color feature are founded out. Then, by using relevance feedback for these images, images which user thought are similar to the example image are found out and then classify these images by spatial position. After that, genetic algorithm is applied to adjust automatically retrieval parameters, reduce the user´s selecting operations in a feedback process, and improve the intelligent degree of the system. By comparative experiments with other two kinds of methods from search efficiency and feed back time, the global accumulated histograms and the partitions and relativity feed backing, this method is proved efficient.
  • Keywords
    content-based retrieval; feature extraction; genetic algorithms; image classification; image colour analysis; image retrieval; relevance feedback; content-based adaptive image retrieval technology; genetic algorithm; global color feature; image classification; image color histogram; relevance feedback; Content based retrieval; Feedback; Feeds; Genetic algorithms; Histograms; Image analysis; Image color analysis; Image retrieval; Information retrieval; Libraries; adaptive image retrieval; color histogram; image classifying; relevance feedback;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Virtual Environments, Human-Computer Interfaces and Measurements Systems, 2009. VECIMS '09. IEEE International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1944-9410
  • Print_ISBN
    978-1-4244-3808-2
  • Electronic_ISBN
    1944-9410
  • Type

    conf

  • DOI
    10.1109/VECIMS.2009.5068868
  • Filename
    5068868