4.2 Article

An Adaptive Visible Watermark Embedding Method based on Region Selection

Journal

SECURITY AND COMMUNICATION NETWORKS
Volume 2021, Issue -, Pages -

Publisher

WILEY-HINDAWI
DOI: 10.1155/2021/6693343

Keywords

-

Funding

  1. National R&D Project of China [2018YFB0803702]

Ask authors/readers for more resources

The paper proposes an adaptive embedding method for visible watermarking to improve the robustness and reduce the risk of malicious removal. By considering the salient and nonsalient regions of the host image, the watermark strength is adaptively calculated and embedded, achieving a good balance between visibility and transparency with high security and ideal visual effect.
Aiming at the problem that the robustness, visibility, and transparency of the existing visible watermarking technologies are difficult to achieve a balance, this paper proposes an adaptive embedding method for visible watermarking. Firstly, the salient region of the host image is detected based on superpixel detection. Secondly, the flat region with relatively low complexity is selected as the embedding region in the nonsalient region of the host image. Then, the watermarking strength is adaptively calculated by considering the gray distribution and image texture complexity of the embedding region. Finally, the visible watermark image is adaptively embedded into the host image with slight adjustment by just noticeable difference (JND) coefficient. The experimental results show that our proposed method improves the robustness of visible watermarking technology and greatly reduces the risk of malicious removal of visible watermark image. Meanwhile, a good balance between the visibility and transparency of the visible watermark image is achieved, which has the advantages of high security and ideal visual effect.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.2
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available