Robust Zero-watermarking Algorithm for Medical Images Based on Maximally Stable Extremal Regions and DCT

Wang, Xue; Li, Jingbing; Bhatti, Uzair Aslam; Huang, Mengxing

doi:10.1109/prai59366.2023.10331946

2023 IEEE 6th International Conference on Pattern Recognition and Artificial Intelligence (PRAI) 2023

DOI: 10.1109/prai59366.2023.10331946

|View full text |Cite

Robust Zero-watermarking Algorithm for Medical Images Based on Maximally Stable Extremal Regions and DCT

Xue Wang,

Jingbing Li,

Uzair Aslam Bhatti

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

A SURF and SVD-based robust zero-watermarking for medical image integrity

Taj,

Tao,

Kanwal

et al. 2024

PLoS ONE

View full text Add to dashboard Cite

Medical image security is paramount in the digital era but remains a significant challenge. This paper introduces an innovative zero-watermarking methodology tailored for medical imaging, ensuring robust protection without compromising image quality. We utilize Sped-up Robust features for high-precision feature extraction and singular value decomposition (SVD) to embed watermarks into the frequency domain, preserving the original image’s integrity. Our methodology uniquely encodes watermarks in a non-intrusive manner, leveraging the robustness of the extracted features and the resilience of the SVD approach. The embedded watermark is imperceptible, maintaining the diagnostic value of medical images. Extensive experiments under various attacks, including Gaussian noise, JPEG compression, and geometric distortions, demonstrate the methodology’s superior performance. The results reveal exceptional robustness, with high Normalized Correlation (NC) and Peak Signal-to-noise ratio (PSNR) values, outperforming existing techniques. Specifically, under Gaussian noise and rotation attacks, the watermark retrieved from the encrypted domain maintained an NC value close to 1.00, signifying near-perfect resilience. Even under severe attacks such as 30% cropping, the methodology exhibited a significantly higher NC compared to current state-of-the-art methods.

show abstract

A SURF and SVD-based robust zero-watermarking for medical image integrity

Taj,

Tao,

Kanwal

et al. 2024

PLoS ONE

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Robust Zero-watermarking Algorithm for Medical Images Based on Maximally Stable Extremal Regions and DCT

Cited by 1 publication

References 22 publications

A SURF and SVD-based robust zero-watermarking for medical image integrity

A SURF and SVD-based robust zero-watermarking for medical image integrity

Contact Info

Product

Resources

About