• DocumentCode
    1618937
  • Title

    Detection of Copy Forgery in Digital Images Based on LPP-SIFT

  • Author

    Baina Su ; Zhu Kaizhen

  • Author_Institution
    Sch. of Electr. Eng., Zhengzhou Univ., Zhengzhou, China
  • fYear
    2012
  • Firstpage
    1773
  • Lastpage
    1776
  • Abstract
    Copy forgery is the most commonly used operation of image forgery. This paper describes a new method based on LPP-SIFT(Locality Preserving Projection- Scale Invariant Feature Transform) features for image forgery detection. The algorithm first extracts SIFT keypoints of an image, and then combines LPP to obtain low-dimensional feature descriptors, the final stage is the keypoints matching. Each pair of matched keypoints of the image are marked with lines between them. If the image has undergone copy-forged operation, these lines will obviously concentrate upon two regions. Experiments demonstrate that the proposed approach is efficient for copy operation and other post-processing forgeries, such as rotation, scaling, and retouching.
  • Keywords
    feature extraction; image representation; image watermarking; object detection; security of data; transforms; LPP-SIFT; SIFT keypoint extraction; copy forgery detection; copy-forged operation; digital images; digital watermarking; image keypoints; locality preserving projection-scale invariant feature transform; low-dimensional feature descriptors; retouching forgery; rotation forgery; scaling forgery; sparse representations; Algorithm design and analysis; Digital images; Educational institutions; Feature extraction; Forgery; Transforms; Vectors; Copy forgery; Image forgery detection; LPP; SIFT;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Control and Electronics Engineering (ICICEE), 2012 International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4673-1450-3
  • Type

    conf

  • DOI
    10.1109/ICICEE.2012.469
  • Filename
    6322759