• DocumentCode
    476961
  • Title

    A context-based fusion algorithm for shape retrieval

  • Author

    El-ghazal, Akrem ; Basir, Otman ; Belkasim, Saeid

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Waterloo, Waterloo, ON
  • fYear
    2008
  • fDate
    June 30 2008-July 3 2008
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Shape-based image retrieval has demonstrated encouraging results in retrieving images based on their content. A large body of research in this area has focused on finding effective shape descriptors to search for query images. Nevertheless, the boundless image content variation makes it impossible for a particular choice of descriptor and an algorithm to be effective for all types of images. It is therefore reasonable to approach the problem by combining a group of descriptors and algorithms. Since the effectiveness of an algorithm/descriptor is image dependent, we maintain that for this strategy to achieve its intended goal, the combination scheme must be dynamic as a function of the query context. This paper proposes a context-based fusion algorithm to integrate several shape-based retrieval techniques. Query context is used to determine the most appropriate technique or combination that yields optimal performance. In testing the proposed algorithm, several experiments were conducted.
  • Keywords
    content-based retrieval; image fusion; image retrieval; learning (artificial intelligence); neural nets; context-based fusion algorithm; image content variation; neural network training; query image search; shape-based image retrieval; Context; co-ranking; fusion; image retrieval; shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Fusion, 2008 11th International Conference on
  • Conference_Location
    Cologne
  • Print_ISBN
    978-3-8007-3092-6
  • Electronic_ISBN
    978-3-00-024883-2
  • Type

    conf

  • Filename
    4632332