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Blind Medical Image Watermarking Based on LBP–DWT for Telemedicine Applications

Authors:
Khaled Hebbache at University of Ouargla
Khaled Hebbache
Oussama Aiadi at University of Ouargla
Oussama Aiadi
Belal Khaldi at University of Ouargla
Belal Khaldi
Benziane Ali at Ziane Achour University of Djelfa
Benziane Ali
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Abstract and Figures

With the increasing use of telemedicine in healthcare, the security and integrity of medical images during transmission have become critical. This paper presents a novel blind watermarking scheme Local Binary Pattern–Discrete Wavelet Transform (LBP–DWT) for medical images based on Local Binary Patterns and the Discrete.Wavelet Transform in frequency domain. We take advantage of the LBP, which is computationally fast, to improve the watermark's resistance to the different kinds of attacks, and maintain the overall visual quality of the watermarked images. In addition, the DWT could offer a high trade-off between robustness and imperceptibility due to the multi-resolution analysis it provides. During embedding, the LL band (approximation coefficients) of the DWT is selected and divided into 3 × 3 blocks. The resulting LBP codes are then XORed with the embedding bits and hidden in the corresponding blocks using the Least Significant Bit technique. Note that the Arnold transform is used during the embedding step to scramble the watermark, which is then vectorized based on the ZigZag fashion to improve the security of the proposed scheme. To evaluate the performance of the proposed method, extensive experiments are conducted on a dataset of medical images. The watermarked images are tested against various attacks, including compression, noise addition, and cropping. The obtained results demonstrate the effectiveness of the proposed techniques.
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Circuits, Systems, and Signal Processing
https://doi.org/10.1007/s00034-025-03023-x
Blind Medical Image Watermarking Based on LBP–DWT
for Telemedicine Applications
Khaled Hebbache1·Oussama Aiadi1,2 ·Belal Khaldi1,2 ·Ali Benziane3
Received: 4 January 2024 / Revised: 21 January 2025 / Accepted: 23 January 2025
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025
Abstract
With the increasing use of telemedicine in healthcare, the security and integrity of med-
ical images during transmission have become critical. This paper presents a novel blind
watermarking scheme Local Binary Pattern–Discrete Wavelet Transform (LBP–DWT)
for medical images based on Local Binary Patterns and the Discrete.Wavelet Transform
in frequency domain. We take advantage of the LBP, which is computationally fast, to
improve the watermark’s resistance to the different kinds of attacks, and maintain the
overall visual quality of the watermarked images. In addition, the DWT could offer
a high trade-off between robustness and imperceptibility due to the multi-resolution
analysis it provides. During embedding, the LL band (approximation coefficients) of
the DWT is selected and divided into 3 ×3 blocks. The resulting LBP codes are then
XORed with the embedding bits and hidden in the corresponding blocks using the
Least Significant Bit technique. Note that the Arnold transform is used during the
embedding step to scramble the watermark, which is then vectorized based on the
ZigZag fashion to improve the security of the proposed scheme. To evaluate the per-
formance of the proposed method, extensive experiments are conducted on a dataset
BKhaled Hebbache
hebbache.khaled@univ-ouargla.dz
Oussama Aiadi
aiadi.oussama@univ-ouargla.dz
Belal Khaldi
khaldi.belal@univ-ouargla.dz
Ali Benziane
a.benziane@univ-djelfa.dz
1Computer Science Department, Kasdi Merbah University, Ghardaia Road, BP.511,
30000 Ouargla, Algeria
2Laboratoire d’Intelligence Artificielle et des Technologies de l’Information (LINATI),
30000 Ouargla, Algeria
3Faculty of Sciences and Technology, University of Ziane Achour, Djelfa, Algeria
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
... In recent years, digital watermarking has garnered significant academic attention as a means of copyright protection for remote sensing imagery. A variety of algorithms specifically designed for this purpose have emerged, many of which are rooted in traditional frequency-based approaches, including those employing cosine domain transformations, multi-scale wavelet analysis, and matrix factorization techniques such as singular value decomposition (SVD) [3][4][5]. These methods utilize spectral transformations and decomposition principles to achieve improvements in the imperceptibility, resilience, and security of the watermark. ...
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