| Autor: |
Deyang Wu, Li Li, Jiayan Wang, Penghui Ma, Zichi Wang, Hanzhou Wu |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Journal of King Saud University: Computer and Information Sciences, Vol 35, Iss 8, Pp 101708- (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1319-1578 |
| DOI: |
10.1016/j.jksuci.2023.101708 |
| Popis: |
The advancement of internet has greatly facilitated development of healthcare technology, particularly in the field of remote diagnosis. However, during the transmission of medical images and electronic medical records through internet, there are risks such as theft, tampering, and compression, which may result in leakage or damage of patients’ information. A robust zero-watermarking scheme using DT CWT and improved differential entropy is proposed to protect the copyright and security of medical images. Firstly, the low-frequency information of medical image is extracted by DT CWT to weaken the impact of non-geometric attacks. Then, a sub-block selection method based on variance is used to select locally stable sub-blocks, and the traditional differential entropy method is improved by introducing singular values and their mean, which improves its robustness against geometric attacks. In order to ensure the security of zero-watermarking, Arnold scrambling and Logistic mapping encryption mechanisms are applied to watermark images. Experimental results show that the proposed scheme provides a high level of robustness with an average normalized correlation value of 0.9928. Compared with other advanced schemes, the robustness of the proposed scheme can be improved by 9 percentage points under the same attacks, which verifies the superiority of the proposed scheme. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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