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Image Duplication Forgery Detection using Two Robust Features

Author Affiliations

  • 1 Department of Computer engineering, Shahrood Branch, Islamic Azad University, Shahrood, IRAN

Res. J. Recent Sci., Volume 1, Issue (12), Pages 1-6, December,2 (2012)


Nowadays duplication forgery is the most applicable method to make tampered images. This method copies a region of an image and pasted into another part(s) of that image. There are several methods to detect forged images. Most of them can only detect those regions which are exactly pasted into another part, but in practice the copied region is scaled or rotated before pasting to achieve the best matching with surrounding. In this paper we propose a method to detect duplicated regions in an image using SIFT features and then using Zernik moments. By using SIFT features we can detect duplicated regions even if they scaled or rotated, but these features cannot find flat duplicated regions. Zernik moments can solve this problem; they can find flat copied regions but failed to find scaled copied regions. So at first we will apply SIFT feature extraction method and find SIFT key points, but there is no SIFT key points in flat regions, then we will apply zernik moments on such regions, So duplicated region in all over the image even in flat regions will detected while the process time is efficient.


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