• DocumentCode
    697815
  • Title

    Automatic TV logo detection and classification in broadcast videos

  • Author

    Ozay, Nedret ; Sankur, Bulent

  • Author_Institution
    Bogazici Univ., Istanbul, Turkey
  • fYear
    2009
  • fDate
    24-28 Aug. 2009
  • Firstpage
    839
  • Lastpage
    843
  • Abstract
    In this study1, we present a fully automatic TV logo identification system. TV logos are detected in static regions given by time-averaged edges subjected to post-processing operations. Once the region of interest of a logo candidate is established, TV logos are recognized via their subspace features. Comparative analysis of features has indicated that ICA-II architecture yields the most discriminative with an accuracy of 99.2% in a database of 3040 logo images (152 varieties). Online tests for both detection and recognition on running videos have achieved 96.0% average accuracy. A more reliable logo identifier will be feasible by improving the accuracy of the extracted logo mask.
  • Keywords
    image classification; object detection; television broadcasting; ICA-II architecture yields; automatic TV logo classification; automatic TV logo detection; broadcast videos; logo identification system; Accuracy; Image edge detection; Principal component analysis; Support vector machines; TV; Vectors; Videos;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference, 2009 17th European
  • Conference_Location
    Glasgow
  • Print_ISBN
    978-161-7388-76-7
  • Type

    conf

  • Filename
    7077387