Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (1)
  • Open Access


    A Survey on Digital Image Copy-Move Forgery Localization Using Passive Techniques

    Weijin Tan1,*, Yunqing Wu1, Peng Wu1, Beijing Chen1,2

    Journal of New Media, Vol.1, No.1, pp. 11-25, 2019, DOI:10.32604/jnm.2019.06219

    Abstract Digital images can be tampered easily with simple image editing software tools. Therefore, image forensic investigation on the authenticity of digital images’ content is increasingly important. Copy-move is one of the most common types of image forgeries. Thus, an overview of the traditional and the recent copy-move forgery localization methods using passive techniques is presented in this paper. These methods are classified into three types: block-based methods, keypoint-based methods, and deep learning-based methods. In addition, the strengths and weaknesses of these methods are compared and analyzed in robustness and computational cost. Finally, further research directions are discussed. More >

Displaying 1-10 on page 1 of 1. Per Page