A Copy Move Forgery Detection to Overcome Sustained Attacks Using Dyadic Wavelet Transform and SIFT Methods

  • Vijay Anand
  • Mohammad Farukh Hashmi
  • Avinash G. Keskar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8397)


In the present digital world integrity and trustworthiness of the digital images is an important issue. And most probably copy- move forgery is used to tamper the digital images. Thus as a solution to this problem, through this paper we proposes a unique and blind method for detecting copy-move forgery using dyadic wavelet transform (DyWT) in combination with scale invariant feature transform (SIFT). First we applied DyWT on a given test image to decompose it into four sub-bands LL, LH, HL, HH. Out of these four sub-bands LL band contains most of the information we intended to apply SIFT on LL part only to extract the key features and using these key features we obtained descriptor vector and then went on finding similarities between various descriptors vector to come to a decision that there has been some copy-move tampering done to the given image. In this paper, we have done a comparative study based on the methods like (a).DyWT (b).DWT and SIFT (c). DyWT and SIFT. Since DyWT is invariant to shift whereas discrete wavelet transform (DWT) is not, thus DyWT is more accurate in analysis of data. And it is shown that by using DyWT with SIFT we are able to extract more numbers of key points that are matched and thus able to detect copy-move forgery more efficiently.


Copy-move forgery Dyadic Wavelet Transform (DyWT) DWT SIFT 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Vijay Anand
    • 1
  • Mohammad Farukh Hashmi
    • 1
  • Avinash G. Keskar
    • 1
  1. 1.Department of Electronics EngineeringVisvesvaraya National Institute of TechnologyNagpurIndia

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