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Object-Removal Forgery Detection Through Reflectance Analysis

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Abstract

While creating digital image forgeries, it is often necessary to hide an object from the image. For instance, to replace a person on a picture one would first remove the person on the image before inserting the new one. This process of suppression can be performed in many ways but almost always involve recreating some background textures. While recreating it, artists sometimes use common tools and apply smooth transitions to seamlessly blend the result. This operation can decrease the created texture sharpness. In this paper, we explore the possibility to reveal this effect to expose possible forgeries.
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Dates and versions

hal-03320799 , version 1 (16-08-2021)

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Gael Mahfoudi, Frederic Morain-Nicolier, Florent Retraint, Marc Pic. Object-Removal Forgery Detection Through Reflectance Analysis. IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 2020, Louisville, United States. pp.1-6, ⟨10.1109/ISSPIT51521.2020.9408870⟩. ⟨hal-03320799⟩
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