Multiple Zero-Watermarking of Medical Images for Internet of Medical Things
The Internet of Medical Things (IoMT) plays a vital role in healthcare systems to increase electronic devices’ accuracy, reliability, and productivity. This paper presents fast multiple zero-watermarking methods based on Multi-channel Fractional Legendre Fourier moments (MFrLFMs) for medi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9751699/ |
| _version_ | 1828280563714228224 |
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| author | Mahmoud Magdy Neveen I. Ghali Said Ghoniemy Khalid M. Hosny |
| author_facet | Mahmoud Magdy Neveen I. Ghali Said Ghoniemy Khalid M. Hosny |
| author_sort | Mahmoud Magdy |
| collection | DOAJ |
| description | The Internet of Medical Things (IoMT) plays a vital role in healthcare systems to increase electronic devices’ accuracy, reliability, and productivity. This paper presents fast multiple zero-watermarking methods based on Multi-channel Fractional Legendre Fourier moments (MFrLFMs) for medical image security and copyright protection in IoMT applications without deforming the original medical images. The MFrLFMs are utilized due to their high accuracy, numerical stability, geometric invariances, and high resistance to various attacks. Based on the most significant features generated from MFrLFMs, after scrambling using a two-dimensional Discrete Henon Map, then XORed with binary scrambled watermark to construct owner share. The proposed watermarking method is implemented using a low-cost Raspberry Pi Linux microprocessor, which ensures the suitability of medical devices in the IoMT environment. We evaluated the robustness of the proposed algorithm against different geometric and common signal processing attacks using various medical images. The proposed method gives better BER, NC, and SSIM values than existing methods. |
| first_indexed | 2024-04-13T08:00:14Z |
| format | Article |
| id | doaj.art-952db63c38a94911aaffcff6bb729d7f |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-13T08:00:14Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-952db63c38a94911aaffcff6bb729d7f2022-12-22T02:55:17ZengIEEEIEEE Access2169-35362022-01-0110388213883110.1109/ACCESS.2022.31658139751699Multiple Zero-Watermarking of Medical Images for Internet of Medical ThingsMahmoud Magdy0https://orcid.org/0000-0001-6109-7297Neveen I. Ghali1Said Ghoniemy2Khalid M. Hosny3https://orcid.org/0000-0001-8065-8977Department of Digital Media Technology, Future University in Egypt (FUE), New Cairo, EgyptDepartment of Digital Media Technology, Future University in Egypt (FUE), New Cairo, EgyptDepartment of Computer Systems, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, EgyptDepartment of Information Technology, Zagazig University, Zagazig, EgyptThe Internet of Medical Things (IoMT) plays a vital role in healthcare systems to increase electronic devices’ accuracy, reliability, and productivity. This paper presents fast multiple zero-watermarking methods based on Multi-channel Fractional Legendre Fourier moments (MFrLFMs) for medical image security and copyright protection in IoMT applications without deforming the original medical images. The MFrLFMs are utilized due to their high accuracy, numerical stability, geometric invariances, and high resistance to various attacks. Based on the most significant features generated from MFrLFMs, after scrambling using a two-dimensional Discrete Henon Map, then XORed with binary scrambled watermark to construct owner share. The proposed watermarking method is implemented using a low-cost Raspberry Pi Linux microprocessor, which ensures the suitability of medical devices in the IoMT environment. We evaluated the robustness of the proposed algorithm against different geometric and common signal processing attacks using various medical images. The proposed method gives better BER, NC, and SSIM values than existing methods.https://ieeexplore.ieee.org/document/9751699/Color medical imageszero-WatermarkingIoMTfractional-order momentsRaspberry-Pi |
| spellingShingle | Mahmoud Magdy Neveen I. Ghali Said Ghoniemy Khalid M. Hosny Multiple Zero-Watermarking of Medical Images for Internet of Medical Things IEEE Access Color medical images zero-Watermarking IoMT fractional-order moments Raspberry-Pi |
| title | Multiple Zero-Watermarking of Medical Images for Internet of Medical Things |
| title_full | Multiple Zero-Watermarking of Medical Images for Internet of Medical Things |
| title_fullStr | Multiple Zero-Watermarking of Medical Images for Internet of Medical Things |
| title_full_unstemmed | Multiple Zero-Watermarking of Medical Images for Internet of Medical Things |
| title_short | Multiple Zero-Watermarking of Medical Images for Internet of Medical Things |
| title_sort | multiple zero watermarking of medical images for internet of medical things |
| topic | Color medical images zero-Watermarking IoMT fractional-order moments Raspberry-Pi |
| url | https://ieeexplore.ieee.org/document/9751699/ |
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