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High-capacity data hiding in encrypted images using MSB prediction

Authors :
Dave Trinel
Pauline Puteaux
William Puech
Image & Interaction (ICAR)
Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM)
Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)
Unité de Glycobiologie Structurale et Fonctionnelle UMR 8576 (UGSF)
Université de Lille-Centre National de la Recherche Scientifique (CNRS)
Unité de Glycobiologie Structurale et Fonctionnelle - UMR 8576 (UGSF)
Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA)
Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)
Institut National de la Recherche Agronomique (INRA)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)
Source :
IPTA, 6th International Conference on Image Processing Theory Tools and Applications, IPTA: Image Processing Theory Tools and Applications, IPTA: Image Processing Theory Tools and Applications, Dec 2016, Oulu, Finland. ⟨10.1109/IPTA.2016.7820991⟩
Publication Year :
2016
Publisher :
IEEE, 2016.

Abstract

International audience; In the last few years, visual privacy has become a major problem. Because of this, encrypted image processing has received a lot of attention within the scientific and business communities. Data hiding in encrypted images (DHEI) is an effective technique to embed data in the encrypted domain. The owner of an image encrypts it with a secret key and it is still possible to embed additional data without knowing the original content nor the secret key. This secret message can be extracted and the initial image can be recovered in the decoding phase. Recently, DHEI has become an investigative field, but the proposed methods do not allow a large amount of embedding capacity. In this paper, we present a new method based on the MSB (most significant bit) prediction. We suggest to hide one bit per pixel by pre-processing the image to avoid prediction errors and, thereby, to improve the quality of the reconstructed image. We have applied our method to various images and, in every cases, the obtained image is very similar to the original one in terms of PSNR or SSIM.

Details

Database :
OpenAIRE
Journal :
2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)
Accession number :
edsair.doi.dedup.....2fd86bf5e0620b7bec8251a646cee266
Full Text :
https://doi.org/10.1109/ipta.2016.7820991