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  • 1.
    Devagiri, Vishnu Manasa
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Cheddad, Abbas
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Splicing Forgery Detection and the Impact of Image Resolution2017In: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON ELECTRONICS, COMPUTERS AND ARTIFICIAL INTELLIGENCE - ECAI 2017, IEEE , 2017Conference paper (Refereed)
    Abstract [en]

    With the development of the Internet, and the increase in the online storage space, there has been an explosion in the volume of videos and images circulating online. An important part of the digital forensics' tasks is to scrutinise part of these images to make important decisions. Digital tampering of images can impede reliability of these decisions. Through this paper we attempt to improve the detection rate of splicing forgery. We also examine how well the examined splicing forgery detection algorithm works on low-resolution images. In this paper, the aim is to enhance the accuracy of an existing algorithm. One tailed Wilcoxon signed rank test was utilised to compare the performance of the different algorithms.

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