• DocumentCode
    508997
  • Title

    Robust Image Copy Detection Using Local Invariant Feature

  • Author

    Zou, Fuhao ; Ling, Hefei ; Li, Xiaowei ; Xu, Zhihua ; Li, Ping

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Huazhong Univ. of Scienec&Technol. Wuhan, Wuhan, China
  • Volume
    1
  • fYear
    2009
  • fDate
    18-20 Nov. 2009
  • Firstpage
    57
  • Lastpage
    61
  • Abstract
    This paper proposes a novel geometric distortion resilient image copy detection scheme based on scale invariant feature transform (SIFT) detector. By using the SIFT detector, the proposed copy detection scheme first construct a series of robust, homogenous, and larger size circular patches. And then, the cirque track division strategy and ordinal measure concept are introduced to generate a cirque-based ordinal measure feature vector for each circular patch. Besides, the ROC graph and MAP probability are utilized to estimate the two parameters (vector dimension and detection threshold) respectively. Experimental results and the related analysis show that the proposed scheme is robust to most of geometric and photometric distortions.
  • Keywords
    object detection; transforms; MAP probability; ROC graph; cirque track division strategy; cirque-based ordinal measure feature vector; detection threshold; geometric distortion resilient image copy detection scheme; geometric distortions; ordinal measure concept; photometric distortions; scale invariant feature transform detector; vector dimension; Computer vision; Data mining; Detectors; Distortion measurement; Feature extraction; Image registration; Noise reduction; Noise robustness; Parameter estimation; Photometry;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Information Networking and Security, 2009. MINES '09. International Conference on
  • Conference_Location
    Hubei
  • Print_ISBN
    978-0-7695-3843-3
  • Electronic_ISBN
    978-1-4244-5068-8
  • Type

    conf

  • DOI
    10.1109/MINES.2009.148
  • Filename
    5368986