Recent advances in computer technology have made digital image tampering more and more common. In this paper we present an approach to passive detection of image splicing. The image splicing detection problem can be regarded as a two-class classification problem under the pattern recognition framework. The features are extracted by image quality metrics (IQMs) and moments of characteristic functions of wavelet subbands. To evaluate the performance of our proposed model, we further present a concrete implementation of this model. Our experimental works have demonstrated that this splicing detection scheme performs effectively and have indicated that the proposed approach possesses promising capability in splicing detection.
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