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In this paper, we use contourlet transform for digital image manipulation detection. We extract contourlet and wavelet features and test these obtained features on a controlled image data set. Results show that contourlet based features gives better success rates than wavelet based ones.
The technologies making possible to change even the content of the digital media are developing fast. The demand for the development of mathematical and computational algorithms to determine the modifications on digital media has arisen and the studies in this area are gaining speed by the day. In this paper, we propose new statistical models for wavelet based transforms and try to differentiate between...
We propose statistical image models for wavelet-based transforms, investigate their use, and compare their relative merits within the context of digital image forensics. We consider the problems of 1) differentiating computer graphics images from photographic images, 2) source camera and source scanner identification, and 3) source artist identification from digital painting samples. The features...
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