• DocumentCode
    2145356
  • Title

    A Similarity Measuring Method Between Image Regions Based on Granular Computing

  • Author

    Shi, Jinling ; Du, Genyuan

  • Author_Institution
    Int. Sch. of Educ., Xuchang Univ., Xuchang, China
  • fYear
    2010
  • fDate
    14-16 Aug. 2010
  • Firstpage
    755
  • Lastpage
    758
  • Abstract
    To effectively measure the similarity between image regions, this paper proposes a new measuring method based on granular computing theory. First, image feature information table is transformed into the type of order matrix by defining the concept of image feature information table, order matrix, feature granular and granular base. Secondly, further study and analysis of order matrix and feature granular with granular computing model are required. Moreover, a similarity measuring method is defined on condition that it doesn´t change the image information based on the concepts of feature values and feature weights. Lastly, a detailed example is given to prove the validity of the similarity measuring method.
  • Keywords
    artificial intelligence; content-based retrieval; image retrieval; feature granular; feature values concept; feature weights concept; granular base; granular computing; image feature information table; image regions; order matrix; similarity measurement method; Computational modeling; Educational institutions; Feature extraction; Image retrieval; Velocity measurement; Weight measurement; granular computing; image feature; order relation; similarity measure;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Granular Computing (GrC), 2010 IEEE International Conference on
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    978-1-4244-7964-1
  • Type

    conf

  • DOI
    10.1109/GrC.2010.27
  • Filename
    5576067