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Fingerprint-based robust medical image watermarking in hybrid transform
To protect the medical images integrity, digital watermark is embedded into the medical images. A non-blind medical image watermarking scheme based on hybrid transform is propounded. In this paper, fingerprint of the patient is used as watermark for better authentication, identifying the original me...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8799990/ https://www.ncbi.nlm.nih.gov/pubmed/35125576 http://dx.doi.org/10.1007/s00371-022-02406-4 |
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author | Vaidya, S. Prasanth |
author_facet | Vaidya, S. Prasanth |
author_sort | Vaidya, S. Prasanth |
collection | PubMed |
description | To protect the medical images integrity, digital watermark is embedded into the medical images. A non-blind medical image watermarking scheme based on hybrid transform is propounded. In this paper, fingerprint of the patient is used as watermark for better authentication, identifying the original medical image and privacy of the patients. In this scheme, lifting wavelet transform (LWT) and discrete wavelet transform (DWT) are utilized for amplifying the watermarking algorithm. The scaling and embedding factors are calculated adaptively with the help of Local Binary Pattern values of the host medical image to achieve better imperceptibility and robustness for medical images and fingerprint watermark, respectively. Two-level decomposition is done where for the first level LWT is utilized and for the second level decomposition DWT is utilized. At the extraction side, non-blind recovery of fingerprint watermark is performed which is similar to the embedding process. The propounded design is implemented on various medical images like Chest X-ray, CT scan and so on. The propounded design provides better imperceptibility and robustness with the combination of LWT–DWT. The result analysis proves that the proposed fingerprint watermarking scheme has attained best results in terms of robustness and authentication with different medical image attacks. Peak Signal to Noise Ratio and Normalized Correlation Coefficient metrics are used for evaluating the proposed scheme. Furthermore, superior results are obtained when compared to related medical image watermarking schemes. |
format | Online Article Text |
id | pubmed-8799990 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-87999902022-01-31 Fingerprint-based robust medical image watermarking in hybrid transform Vaidya, S. Prasanth Vis Comput Original Article To protect the medical images integrity, digital watermark is embedded into the medical images. A non-blind medical image watermarking scheme based on hybrid transform is propounded. In this paper, fingerprint of the patient is used as watermark for better authentication, identifying the original medical image and privacy of the patients. In this scheme, lifting wavelet transform (LWT) and discrete wavelet transform (DWT) are utilized for amplifying the watermarking algorithm. The scaling and embedding factors are calculated adaptively with the help of Local Binary Pattern values of the host medical image to achieve better imperceptibility and robustness for medical images and fingerprint watermark, respectively. Two-level decomposition is done where for the first level LWT is utilized and for the second level decomposition DWT is utilized. At the extraction side, non-blind recovery of fingerprint watermark is performed which is similar to the embedding process. The propounded design is implemented on various medical images like Chest X-ray, CT scan and so on. The propounded design provides better imperceptibility and robustness with the combination of LWT–DWT. The result analysis proves that the proposed fingerprint watermarking scheme has attained best results in terms of robustness and authentication with different medical image attacks. Peak Signal to Noise Ratio and Normalized Correlation Coefficient metrics are used for evaluating the proposed scheme. Furthermore, superior results are obtained when compared to related medical image watermarking schemes. Springer Berlin Heidelberg 2022-01-29 2023 /pmc/articles/PMC8799990/ /pubmed/35125576 http://dx.doi.org/10.1007/s00371-022-02406-4 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Article Vaidya, S. Prasanth Fingerprint-based robust medical image watermarking in hybrid transform |
title | Fingerprint-based robust medical image watermarking in hybrid transform |
title_full | Fingerprint-based robust medical image watermarking in hybrid transform |
title_fullStr | Fingerprint-based robust medical image watermarking in hybrid transform |
title_full_unstemmed | Fingerprint-based robust medical image watermarking in hybrid transform |
title_short | Fingerprint-based robust medical image watermarking in hybrid transform |
title_sort | fingerprint-based robust medical image watermarking in hybrid transform |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8799990/ https://www.ncbi.nlm.nih.gov/pubmed/35125576 http://dx.doi.org/10.1007/s00371-022-02406-4 |
work_keys_str_mv | AT vaidyasprasanth fingerprintbasedrobustmedicalimagewatermarkinginhybridtransform |