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Optical fragile zero-watermarking scheme for medical image tampering detection

Aug 2026 · Physica Scripta · Vol 101 · 0 citations · 49 references
Physics

Abstract

Current optical image watermarking methods are mostly robust techniques aimed at image copyright protection, and the few existing optical fragile watermarking methods for image tamper detection are almost exclusively designed for natural images. To address these issues, this paper proposes an optical fragile zero-watermarking (ZW) method specifically for medical image tamper detection. In the proposed method, the two-dimensional discrete wavelet transform is first utilized to extract the high-frequency polarity features of the medical host image, which are then combined with the SHA-256 hash algorithm to generate chaotic initial state values. Secondly, these initial values are used to dynamically initialize a novel three-dimensional chaotic system (3D-CCSLM) to generate a chaotic sequence, realizing a ‘one-image-one-key’ security mechanism. Subsequently, a cascaded dual-phase mask architecture is introduced during the watermark’s optical encryption stage, where the original watermark sequentially undergoes double Fresnel diffraction and phase truncation operations to form an optical ciphertext; this ciphertext is then diffused by the chaotic sequence and XORed with the host features to generate a ZW certificate to be stored in the database. Extensive experimental results demonstrate that the proposed scheme achieves complete recovery of the copyright watermark under ideal, attack-free conditions and possesses high algorithmic execution efficiency. By integrating the hash avalanche effect with a cascaded optical encryption architecture, the scheme achieves acute fragility against localized tampering, enabling highly sensitive integrity alarms. Furthermore, the noise-like distribution of the generated ZW effectively neutralizes statistical attacks. Ultimately, this zero-distortion approach provides a highly secure and reliable solution for the authentication and integrity verification of sensitive medical imagery.

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