A fragile zero-watermarking method based on dual quaternion matrix decomposition

2025-10-31

AI Summary

Medical images face two critical security risks during transmission and sharing: ambiguous copyright ownership and vulnerability to unauthorized content tampering. To address these challenges, this paper proposes a fragile zero-watermarking method based on dual quaternion matrix decomposition. The approach models structural image features by exploiting the intrinsic algebraic relationship between the standard and dual parts of dual quaternions, and employs low-rank matrix decomposition to extract stable features that are simultaneously robust against benign distortions and sensitive to malicious alterations. The resulting zero-watermarking scheme is embedding-free and lossless, requiring no modification to the original image. It enables fine-grained copyright authentication and pixel-level tamper localization. Experimental results demonstrate high sensitivity—accurately detecting minute tampering—strong robustness against common signal processing operations (e.g., JPEG compression, filtering), and computational efficiency. The method thus offers practical utility for securing medical imaging data.

Technology Category

• Computer Vision: Medical and Biological Imaging
• Machine Learning: Privacy
• Application Domains: Security

Application Category

• Security and Privacy: Data transparency and provenance
• Responsible Web: Data and user privacy-enhancing technologies for the Web
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity

Abstract

Medical images play a crucial role in assisting diagnosis, remote consultation, and academic research. However, during the transmission and sharing process, they face serious risks of copyright ownership and content tampering. Therefore, protecting medical images is of great importance. As an effective means of image copyright protection, zero-watermarking technology focuses on constructing watermarks without modifying the original carrier by extracting its stable features, which provides an ideal approach for protecting medical images. This paper aims to propose a fragile zero-watermarking model based on dual quaternion matrix decomposition, which utilizes the operational relationship between the standard part and the dual part of dual quaternions to correlate the original carrier image with the watermark image, and generates zero-watermarking information based on the characteristics of dual quaternion matrix decomposition, ultimately achieving copyright protection and content tampering detection for medical images.

Problem

• Protecting medical images from copyright infringement
• Detecting content tampering during image transmission
• Constructing watermarks without modifying original medical images

Innovation

• Dual quaternion matrix decomposition for fragile zero-watermarking
• Linking image and watermark via dual quaternion operations
• Generates zero-watermarking without modifying original medical images