• DocumentCode
    448826
  • Title

    Keyword-detection approach to automatic image annotation

  • Author

    Viitaniemi, Ville ; Laaksonen, Jorma

  • Author_Institution
    Neural Networks Res. Centre, Helsinki Univ. of Technol., Espoo, Finland
  • fYear
    2005
  • fDate
    Nov. 30 2005-Dec. 1 2005
  • Firstpage
    15
  • Lastpage
    22
  • Abstract
    In this paper we consider the problem of automatically annotating images with keywords. We first discuss performance measures for the problem in some length. We propose a new information-theory based measure de-symmetrised mutual information (DTMI). We then describe a straightforward solution to the annotation problem. We first train a set of classifiers to detect the presence of each individual keyword in the set of training images. For this we use the PicSOM image analysis framework. We then describe a method of converting the classifier outputs back into keyword annotations for the test set. We compare the performance of the proposed method experimentally to that of other methods presented in the literature. For the experiments we use data from the Corel database. The result of the comparison is favourable to the proposed method.
  • Keywords
    image classification; image matching; information retrieval; information theory; Corel database; PicSOM; automatic image annotation; desymmetrised mutual information; image analysis; information theory; keyword detection;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Integration of Knowledge, Semantics and Digital Media Technology, 2005. EWIMT 2005. The 2nd European Workshop on the (Ref. No. 2005/11099)
  • Conference_Location
    London
  • ISSN
    0537-9989
  • Print_ISBN
    0-86341-595-4
  • Type

    conf

  • Filename
    1575945