• DocumentCode
    2055135
  • Title

    A System for Automatic Image Categorization

  • Author

    Moscato, Vincenzo ; Picariello, Antonio ; Persia, Fabio ; Penta, Antonio

  • Author_Institution
    Dipt. di Inf. e Sist., Univ. of Naples, Naples, Italy
  • fYear
    2009
  • fDate
    14-16 Sept. 2009
  • Firstpage
    624
  • Lastpage
    629
  • Abstract
    Traditional multimedia classification techniques are based on the analysis of either low-level features or annotated textual information. Instead, the semantic gap between rough data and its content is still a challenging task. In this paper, we describe a novel solution which automatically associates the image analysis and processing algorithms to keywords and human annotation. We use the well known FLICK system, that contains images, tags, keywords and sometimes useful annotation describing both the content of an image and personal interesting information describing the scene. We have carried out several experiments demonstrating that the proposed categorization process achieves quite good performances in terms of efficiency and effectiveness.
  • Keywords
    image classification; multimedia computing; annotated textual information; automatic image categorization; human annotation; image analysis; multimedia classification; rough data; semantic gap; Content based retrieval; Humans; Image analysis; Image classification; Image retrieval; Indexing; Multimedia computing; Multimedia systems; Tagging; Taxonomy; image categorization; image indexing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantic Computing, 2009. ICSC '09. IEEE International Conference on
  • Conference_Location
    Berkeley, CA
  • Print_ISBN
    978-1-4244-4962-0
  • Electronic_ISBN
    978-0-7695-3800-6
  • Type

    conf

  • DOI
    10.1109/ICSC.2009.25
  • Filename
    5298690