• DocumentCode
    2788127
  • Title

    Detection of digital doctoring in exemplar-based inpainted images

  • Author

    Wu, Qiong ; Sun, Shao-jie ; Zhu, Wei ; LI, Guo-hui ; Tu, Dan

  • Author_Institution
    Coll. of Inf. Syst. & Manage., Nat. Univ. of Defense Technol., Changsha
  • Volume
    3
  • fYear
    2008
  • fDate
    12-15 July 2008
  • Firstpage
    1222
  • Lastpage
    1226
  • Abstract
    Exemplar-based inpainting technique can be used to remove objects from an image and play visual tricks, which would affect the authenticity of images. In this paper, a blind detection method based on zero-connectivity feature and fuzzy membership is proposed to detect the specific doctoring. Firstly, zero-connectivity labeling is applied on block pairs to yield matching degree feature for all blocks in the region of suspicious, and fuzzy memberships are computed by constructing ascending semi-trapezoid membership function. Then the tampered regions are identified by a cut set. A num of natural and inpainted forged images are used to show the effectiveness of our method in detecting digital doctoring.
  • Keywords
    feature extraction; fuzzy set theory; image matching; digital doctoring detection; exemplar-based inpainted images; fuzzy membership; image authenticity; semitrapezoid membership function; zero-connectivity features; zero-connectivity labeling; Cybernetics; Digital images; Filling; Forensics; Forgery; Labeling; Machine learning; Machine learning algorithms; Object detection; Sun; Digital doctoring; Exemplar-based inpainting; Fuzzy membership; Zero-connectivity labeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2008 International Conference on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-2095-7
  • Electronic_ISBN
    978-1-4244-2096-4
  • Type

    conf

  • DOI
    10.1109/ICMLC.2008.4620591
  • Filename
    4620591