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Reversible Privacy Protection with the Capability of Antiforensics
Author(s) -
Liyun Dou,
Zichi Wang,
Zhenxing Qian,
Guorui Feng
Publication year - 2021
Publication title -
security and communication networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.446
H-Index - 43
eISSN - 1939-0114
pISSN - 1939-0122
DOI - 10.1155/2021/5558873
Subject(s) - inpainting , computer science , privacy protection , scheme (mathematics) , image (mathematics) , object (grammar) , artificial intelligence , computer vision , information hiding , task (project management) , data protection act 1998 , dual (grammatical number) , noise (video) , data mining , computer security , art , mathematical analysis , mathematics , management , literature , economics
In this paper, we propose a privacy protection scheme using image dual-inpainting and data hiding. In the proposed scheme, the privacy contents in the original image are concealed, which are reversible that the privacy content can be perfectly recovered. We use an interactive approach to select the areas to be protected, that is, the protection data. To address the disadvantage that single image inpainting is susceptible to forensic localization, we propose a dual-inpainting algorithm to implement the object removal task.-e protection data is embedded into the image with object removed using a popular data hiding method.We further use the pattern noise forensic detection and the objective metrics to assess the proposed method. -e results on different scenarios show that the proposed scheme can achieve better visual quality and antiforensic capability than the state-of-the-art works.

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