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Multi-object splicing forgery detection using noise level difference
Liu B.; Pun C.-M.
Source Publication2017 IEEE Conference on Dependable and Secure Computing
AbstractSplicing forgery is a commonly used operation in digital image synthesize. Exposing multi-object splicing forgery by detecting noise discrepancy is discussed in this paper. The image is firstly segmented into small segments and noise level function, which reveals relationship between image noise and pixels' intensity is estimated. Suspicious regions are detected by checking constrains of noise level function. In the experiment, a new dataset is used for evaluating the proposed method. The experimental results show the effectiveness and robustness in dealing with multi-objects splicing forgery. Besides, comparisons prove our method is superior to the existing state-of-art.
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Document TypeConference paper
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Liu B.,Pun C.-M.. Multi-object splicing forgery detection using noise level difference[C],2017:533-534.
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