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Öğe A Comparison of Wavelet Family of Transforms from Image Forensics Perspective(Turgut Ozal Univ, 2012) Ozparlak, Levent; Avcibas, IsmailIn this study, we compare wavelet based transforms for the cases of different image forensics problems. We extract wavelet based features and make experiments for different problems. The results show that a mixture of wavelet based features give the best performance in each experiment. In the absence of such a classifier with mixed features, the best performing features were obtained from contourlet transform coefficients.Öğe Differentiating Between Images Using Wavelet-Based Transforms: A Comparative Study(Ieee-Inst Electrical Electronics Engineers Inc, 2011) Ozparlak, Levent; Avcibas, IsmailWe 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 obtained from ridgelet and contourlet transform-based image models almost always perform better than the features obtained from wavelet-based image models for the problems at hand. We outline properties of efficient image representation, relate these properties to wavelet-based transforms, and discuss the experimental results in relation to the model properties.












