Abstract
One of the most frequently used types of image forgery is embedding another image fragment in some part of the image. In this article a methods for this type of forgeries detection is proposed. The method is based on the analysis of traces introduced by the camera sensor used to obtain an image. The analyzed image is divided into blocks, for each block we calculate a criterion valued determining the probability of presence/absence of CFA artifacts and, as a consequence, the probability of whether the block is a forgery is calculated. In the experimental part of the work, the accuracy of the detection of the embedded regions is analyzed. We also analyze the robustness of the proposed algorithm to various types of distortions: additive Gaussian noise, JPEG compression and linear contrast enhancement. The results of the experiments showed that the method makes it possible to detect embedded regions of various nature, shape and size, and is also robust to additive Gaussian noise and linear contrast enhancement for a given range of distortions parameters, but is not robust to JPEG compression. A distinctive feature of the method is the ability to identify embedded regions with a minimum size of \(2\times \) 2 pixels.
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Acknowledgements
This work was supported by the Federal Agency of scientific organization (Agreement 007-3/43363/26) in part “The proposed forgery detection method” and by the Russian Foundation for Basic Research (no. 17-29-03190) in part “Experimental results”.
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Kuznetsov, A. (2018). Camera Sensor Traces Analysis in Image Forgery Detection Problem. In: Chmielewski, L., Kozera, R., Orłowski, A., Wojciechowski, K., Bruckstein, A., Petkov, N. (eds) Computer Vision and Graphics. ICCVG 2018. Lecture Notes in Computer Science(), vol 11114. Springer, Cham. https://doi.org/10.1007/978-3-030-00692-1_39
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DOI: https://doi.org/10.1007/978-3-030-00692-1_39
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