Electronics Department, Faculty of Engineering Sciences, Laboratories of Automation and Signals of Annaba (LASA), Badji Mokhtar Annaba University, 23000, Annaba, Algeria.
Computer Science Department, Faculty of Sciences and Technology, Artificial Intelligence and Information Technology Laboratory (LINATI), University of Kasdi Merbah, 30000, Ouargla, Algeria.
Forensic Sci Int. 2021 Mar;320:110691. doi: 10.1016/j.forsciint.2021.110691. Epub 2021 Jan 13.
In this work, we propose a blind watermarking approach for medical image protection. In this approach, the watermark will be constituted of the Electronic Patient Record and the image acquisition data. In order to enhance the security and guarantee the data integrity, the Electronic Patient Record hash will be added to the watermark. The integration process is based on a DWT-SVD combination, a DWT is applied to the retinal image, then, an SVD is applied to the LL sub-band. The watermark will be then integrated into the least significant bits of the S component obtained by combining the parity of the successive coefficients. Experimental results for imperceptibility and robustness show that the proposed scheme maintains a high quality watermarked image and remains highly robust against several conventional attacks.
在这项工作中，我们提出了一种用于医学图像保护的盲水印方法。在这种方法中，水印将由电子病历和图像采集数据组成。为了提高安全性并保证数据完整性，将电子病历哈希添加到水印中。集成过程基于 DWT-SVD 组合，对视网膜图像进行 DWT，然后对 LL 子带进行 SVD。水印将被合并到通过合并连续系数的奇偶校验获得的 S 分量的最低有效位中。对于不可感知性和鲁棒性的实验结果表明，所提出的方案保持了高质量的水印图像，并对几种常见的攻击保持高度的鲁棒性。
