Abstract
Looking for modification traces of digital media is of great value for forensic analysis. The median filter can be used to remove the fingerprints left by other image operations, and the detection of median filtering has become more and more significant. In this paper, a new detector for median-filtering operation is proposed. In the method, the image features combined by LBP (Local Binary Pattern) and coefficient-pair histogram in DCT (Discrete Cosine Transform) domain are firstly extracted; then classifier SVM is used to train the authentic and median-filtered image; lastly, some suspicious images are used to test the effectiveness of the proposed scheme. Large amounts of experiments show that the proposed method can detect median filtering under a variety of scenarios, and further more it has letter robustness against JPEG post-compressed image, this outperforms the existing state-of-the-art method.
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Lai, YN., Gao, TG., Li, JX., Sheng, GR. (2015). Forensic Detection of Median Filtering in Digital Images Using the Coefficient-Pair Histogram of DCT Value and LBP Pattern. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in Computer Science(), vol 9225. Springer, Cham. https://doi.org/10.1007/978-3-319-22180-9_41
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DOI: https://doi.org/10.1007/978-3-319-22180-9_41
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