Visible to the public A Robust Associative Watermarking Technique Based on Frequent Pattern Mining and Texture Analysis

TitleA Robust Associative Watermarking Technique Based on Frequent Pattern Mining and Texture Analysis
Publication TypeConference Paper
Year of Publication2016
AuthorsGhadi, Musab, Laouamer, Lamri, Nana, Laurent, Pascu, Anca
Conference NameProceedings of the 8th International Conference on Management of Digital EcoSystems
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4267-4
Keywordscomposability, confinement, digital watermarking, frequent pattern mining, Human Behavior, image authentication, image mining, pubcrawl, Resiliency, Robustness
Abstract

Nowadays, the principle of image mining plays a vital role in various areas of our life, where numerous frameworks based on image mining are proposed for object recognition, object tracking, sensing images and medical image diagnosis. Nevertheless, the research in the image authentication based on image mining is still confined. Therefore, this paper comes to present an efficient engagement between the frequent pattern mining and digital watermarking to contribute significantly in the authentication of images transmitted via public networks. The proposed framework exploits some robust features of image to extract the frequent patterns in the image data. The maximal relevant patterns are used to discriminate between the textured and smooth blocks within the image, where the texture blocks are more appropriate to embed the secret data than smooth blocks. The experiment's result proves the efficiency of the proposed framework in terms of stabilization and robustness against different kind of attacks. The results are interesting and remarkable to preserve the image authentication.

URLhttp://doi.acm.org/10.1145/3012071.3012101
DOI10.1145/3012071.3012101
Citation Keyghadi_robust_2016