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Blind forensics tool of falsification for RAW images

Abstract : This paper presents a novel method for blind forgery detection of natural image in RAW format. The approach is based on a statistical noise model of natural RAW images. This model is characterized by two parameters which are used as a fingerprint to falsification identification. The identification is cast in the framework of the hypothesis testing theory. For practice use, the Generalized Likelihood Ratio Test (GLRT) is presented and its performance is theoretically established in case of unknown parameters where an estimation of those parameters is designed. Experiments with simulated and real images highlight the relevance of the proposed approach.
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Contributor : Jean-Baptiste Vu Van Connect in order to contact the contributor
Submitted on : Wednesday, July 1, 2020 - 3:54:08 PM
Last modification on : Friday, August 27, 2021 - 3:14:07 PM






Thi Ngoc Canh Doan, Florent Retraint, Cathel Zitzmann. Blind forensics tool of falsification for RAW images. 2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Dec 2017, Bilbao, Spain. pp.018-023, ⟨10.1109/ISSPIT.2017.8388312⟩. ⟨hal-02886536⟩



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