• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

混合变换中基于指纹的鲁棒医学图像水印技术

Fingerprint-based robust medical image watermarking in hybrid transform.

作者信息

Vaidya S Prasanth

机构信息

Department of Computer Science and Engineering, Aditya Engineering College (A), Surampalem, Andhra Pradesh 533437 India.

出版信息

Vis Comput. 2023;39(6):2245-2260. doi: 10.1007/s00371-022-02406-4. Epub 2022 Jan 29.

DOI:10.1007/s00371-022-02406-4
PMID:35125576
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8799990/
Abstract

To protect the medical images integrity, digital watermark is embedded into the medical images. A non-blind medical image watermarking scheme based on hybrid transform is propounded. In this paper, fingerprint of the patient is used as watermark for better authentication, identifying the original medical image and privacy of the patients. In this scheme, lifting wavelet transform (LWT) and discrete wavelet transform (DWT) are utilized for amplifying the watermarking algorithm. The scaling and embedding factors are calculated adaptively with the help of Local Binary Pattern values of the host medical image to achieve better imperceptibility and robustness for medical images and fingerprint watermark, respectively. Two-level decomposition is done where for the first level LWT is utilized and for the second level decomposition DWT is utilized. At the extraction side, non-blind recovery of fingerprint watermark is performed which is similar to the embedding process. The propounded design is implemented on various medical images like Chest X-ray, CT scan and so on. The propounded design provides better imperceptibility and robustness with the combination of LWT-DWT. The result analysis proves that the proposed fingerprint watermarking scheme has attained best results in terms of robustness and authentication with different medical image attacks. Peak Signal to Noise Ratio and Normalized Correlation Coefficient metrics are used for evaluating the proposed scheme. Furthermore, superior results are obtained when compared to related medical image watermarking schemes.

摘要

为保护医学图像的完整性，将数字水印嵌入到医学图像中。提出了一种基于混合变换的非盲医学图像水印方案。在本文中，将患者指纹用作水印以实现更好的认证，从而识别原始医学图像和患者隐私。在该方案中，提升小波变换（LWT）和离散小波变换（DWT）被用于增强水印算法。借助宿主医学图像的局部二值模式值自适应地计算缩放因子和嵌入因子，分别为医学图像和指纹水印实现更好的不可感知性和鲁棒性。进行两级分解，其中第一级使用LWT，第二级分解使用DWT。在提取端，执行与嵌入过程类似的指纹水印非盲恢复。所提出的设计在胸部X光、CT扫描等各种医学图像上得以实现。所提出的设计通过LWT - DWT的组合提供了更好的不可感知性和鲁棒性。结果分析证明，所提出的指纹水印方案在针对不同医学图像攻击的鲁棒性和认证方面取得了最佳结果。使用峰值信噪比和归一化相关系数指标来评估所提出的方案。此外，与相关医学图像水印方案相比，获得了更优的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/cd9de0c2edad/371_2022_2406_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/0f11c558990b/371_2022_2406_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/73af3deb034b/371_2022_2406_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/115fcf9c5217/371_2022_2406_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/761861b5bfc2/371_2022_2406_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/29643135a33b/371_2022_2406_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/d90b034b8191/371_2022_2406_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/d3afbdc2977d/371_2022_2406_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/497fd6a583e3/371_2022_2406_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/520aea960429/371_2022_2406_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/c269fa804b57/371_2022_2406_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/c5f8957f0c4a/371_2022_2406_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/cd9de0c2edad/371_2022_2406_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/0f11c558990b/371_2022_2406_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/73af3deb034b/371_2022_2406_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/115fcf9c5217/371_2022_2406_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/761861b5bfc2/371_2022_2406_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/29643135a33b/371_2022_2406_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/d90b034b8191/371_2022_2406_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/d3afbdc2977d/371_2022_2406_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/497fd6a583e3/371_2022_2406_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/520aea960429/371_2022_2406_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/c269fa804b57/371_2022_2406_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/c5f8957f0c4a/371_2022_2406_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2492/8799990/cd9de0c2edad/371_2022_2406_Fig12_HTML.jpg

相似文献

1
Fingerprint-based robust medical image watermarking in hybrid transform.混合变换中基于指纹的鲁棒医学图像水印技术
Vis Comput. 2023;39(6):2245-2260. doi: 10.1007/s00371-022-02406-4. Epub 2022 Jan 29.
2
A robust semi-fragile watermarking system using Pseudo-Zernike moments and dual tree complex wavelet transform for social media content authentication.一种使用伪泽尼克矩和双树复数小波变换的用于社交媒体内容认证的稳健半脆弱水印系统。
Multimed Tools Appl. 2023 Apr 13:1-53. doi: 10.1007/s11042-023-15177-4.
3
Robust, imperceptible and optimized watermarking of DICOM image using Schur decomposition, LWT-DCT-SVD and its authentication using SURF.基于Schur分解、LWT-DCT-SVD的稳健、不可感知且优化的DICOM图像水印及其基于SURF的认证
Multimed Tools Appl. 2023;82(11):16555-16589. doi: 10.1007/s11042-022-14002-8. Epub 2022 Sep 27.
4
A novel watermarking scheme for medical image using support vector machine and lifting wavelet transform.一种基于支持向量机和提升小波变换的医学图像水印新方案。
Multimed Tools Appl. 2023 Apr 1:1-20. doi: 10.1007/s11042-023-15144-z.
5
A Hybrid Robust Image Watermarking Method Based on DWT-DCT and SIFT for Copyright Protection.一种基于离散小波变换-离散余弦变换和尺度不变特征变换的混合鲁棒图像水印方法用于版权保护。
J Imaging. 2021 Oct 19;7(10):218. doi: 10.3390/jimaging7100218.
6
A sophisticated and provably grayscale image watermarking system using DWT-SVD domain.一种使用离散小波变换-奇异值分解（DWT-SVD）域的复杂且可验证的灰度图像水印系统。
Vis Comput. 2022 Jul 1:1-21. doi: 10.1007/s00371-022-02587-y.
7
A DWT-SVD based robust digital watermarking for medical image security.基于 DWT-SVD 的医学图像安全鲁棒数字水印
Forensic Sci Int. 2021 Mar;320:110691. doi: 10.1016/j.forsciint.2021.110691. Epub 2021 Jan 13.
8
Blind video watermarking scheme for medical video authentication.用于医学视频认证的盲视频水印方案。
Heliyon. 2023 Sep 7;9(9):e19809. doi: 10.1016/j.heliyon.2023.e19809. eCollection 2023 Sep.
9
An Efficient Watermarking Approach Based on LL and HH Edges of DWT-SVD.一种基于离散小波变换-奇异值分解的低频和高频边缘的高效水印方法。
SN Comput Sci. 2021;2(2):82. doi: 10.1007/s42979-021-00478-y. Epub 2021 Feb 8.
10
A robust and secured fusion based hybrid medical image watermarking approach using RDWT-DWT-MSVD with Hyperchaotic system-Fibonacci Q Matrix encryption.一种基于RDWT-DWT-MSVD并结合超混沌系统-斐波那契Q矩阵加密的稳健且安全的融合式混合医学图像水印方法。
Multimed Tools Appl. 2023 Mar 22:1-23. doi: 10.1007/s11042-023-15001-z.

引用本文的文献

1
A robust fragile watermarking approach for image tampering detection and restoration utilizing hybrid transforms.一种利用混合变换的用于图像篡改检测与恢复的鲁棒脆弱水印方法。
Sci Rep. 2025 May 21;15(1):17645. doi: 10.1038/s41598-025-01297-4.
2
Secure healthcare data management using multimodal image fusion and dual watermarking.使用多模态图像融合和双重水印技术进行安全的医疗数据管理。
Sci Rep. 2025 Mar 17;15(1):9047. doi: 10.1038/s41598-025-93544-x.
3
A Highly Robust Medical Image Watermarking Method for Medical Real-time Applications.

本文引用的文献

1
Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: Taxonomy analysis, challenges, future solutions and methodological aspects.基于评估和基准的 COVID-19 医学图像检测和分类的人工智能技术的系统评价：分类分析、挑战、未来解决方案和方法学方面。
J Infect Public Health. 2020 Oct;13(10):1381-1396. doi: 10.1016/j.jiph.2020.06.028. Epub 2020 Jul 1.
2
Secured Medical Images - a Chaotic Pixel Scrambling Approach.安全医学图像——一种混沌像素置乱方法。
J Med Syst. 2016 Nov;40(11):232. doi: 10.1007/s10916-016-0611-5. Epub 2016 Sep 21.
3
一种用于医学实时应用的高度鲁棒的医学图像水印方法。
J Med Signals Sens. 2023 Jul 12;13(3):199-207. doi: 10.4103/jmss.jmss_15_22. eCollection 2023 Jul-Sep.
4
WatMIF: Multimodal Medical Image Fusion-Based Watermarking for Telehealth Applications.WatMIF：用于远程医疗应用的基于多模态医学图像融合的水印技术
Cognit Comput. 2022 Jul 7:1-17. doi: 10.1007/s12559-022-10040-4.
5
Signing and Verifying Encrypted Medical Images Using Double Random Phase Encryption.使用双随机相位加密技术对加密医学图像进行签名和验证
Entropy (Basel). 2022 Apr 12;24(4):538. doi: 10.3390/e24040538.
Image quality assessment: from error visibility to structural similarity.
图像质量评估：从误差可见性到结构相似性。
IEEE Trans Image Process. 2004 Apr;13(4):600-12. doi: 10.1109/tip.2003.819861.