Medical Image Authentication and Self-Recovery Using Fragile Watermarking in the Frequency Domain

The rapid growth in digital image sharing, driven by advancements in internet and communication technologies, has raised concerns about image integrity, especially in sensitive fields like healthcare. This paper presents a fully blind fragile watermarking technique for authenticating and self-recovering color and grayscale medical images. The approach applies the Discrete Wavelet Transform (DWT) to the cover image, and the resulting subbands are divided into 3×3 blocks. One authentication and four recovery watermarks are then embedded into the least significant bits (LSBs) of each block. During the extraction phase, if tampering is detected, the model accurately localizes the altered areas, and a three-level recovery process, including a new inpainting technique, is used to recover the original image. Results based on two publically available datasets demonstrate that this method delivers high-quality watermarked images, achieves optimal watermark extraction accuracy, and maintains high sensitivity to various attacks. Additionally, it provides precise tamper localization and delivers high-quality recovered images, even with tampering rates as high as 60%.

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Publication Details

Published
2025-01-09
DOI
https://doi.org/10.1109/ipas63548.2025.10924548
Citations
1
Primary Topic
Advanced Steganography and Watermarking Techniques
Type
article
Field-Weighted Citation Impact
1.28
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article

Medical Image Authentication and Self-Recovery Using Fragile Watermarking in the Frequency Domain

Nabil Zerrouki, Feryel Souami, Fatma Zohra Bellala, Riadh Bouarroudj et al.
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Advanced Steganography and Watermarking Techniques
1.28
article

Medical Image Authentication and Self-Recovery Using Fragile Watermarking in the Frequency Domain

Nabil Zerrouki, Feryel Souami, Fatma Zohra Bellala, Riadh Bouarroudj, Fouzi Harrou, Ying Sun
article en
1 citations

Abstract

The rapid growth in digital image sharing, driven by advancements in internet and communication technologies, has raised concerns about image integrity, especially in sensitive fields like healthcare. This paper presents a fully blind fragile watermarking technique for authenticating and self-recovering color and grayscale medical images. The approach applies the Discrete Wavelet Transform (DWT) to the cover image, and the resulting subbands are divided into 3×3 blocks. One authentication and four recovery watermarks are then embedded into the least significant bits (LSBs) of each block. During the extraction phase, if tampering is detected, the model accurately localizes the altered areas, and a three-level recovery process, including a new inpainting technique, is used to recover the original image. Results based on two publically available datasets demonstrate that this method delivers high-quality watermarked images, achieves optimal watermark extraction accuracy, and maintains high sensitivity to various attacks. Additionally, it provides precise tamper localization and delivers high-quality recovered images, even with tampering rates as high as 60%.

University of Sciences and Technology Houari Boumediene (DZ), University of Algiers Benyoucef Benkhedda (DZ), King Abdullah University of Science and Technology (SA)
Zero hunger
Openalex Percentile: Top 22%
Advanced Steganography and Watermarking Techniques
1.28
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