• DocumentCode
    1789011
  • Title

    Speeding-up SIFT based copy move forgery detection using level set approach

  • Author

    Sudhakar, K. ; Sandeep, V.M. ; Kulkarni, Santosh

  • Author_Institution
    J.P.N. Coll. of Eng., Telangana, India
  • fYear
    2014
  • fDate
    10-11 Oct. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents an efficient method to detect Copy Move Forgery using SIFT features and the volume of these features is heavily reduced by Chan-Vese´s Level Set approach. Multiple-forged object detection, invariant to scale and rotation, high speed, its simplicity in implementation and robustness are some of this method´s strengths.
  • Keywords
    object detection; transforms; SIFT based copy move forgery detection; SIFT features; level set approach; multiple-forged object detection; scale invariant feature transform; Feature extraction; Forgery; Image edge detection; Image segmentation; Level set; Robustness; Time complexity; Chan-Vese Level Sets; Copy Move Forgery Detection; Key-points; Region of Interest; SIFT; Time complexity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Electronics, Computers and Communications (ICAECC), 2014 International Conference on
  • Conference_Location
    Bangalore
  • Type

    conf

  • DOI
    10.1109/ICAECC.2014.7002407
  • Filename
    7002407
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1789011