Detection of alterations in watermarked medical images using Fast Fourier Transform and Complex-Valued Neural Network
Medical images contain diagnostic information which can be used for early detection of diseases. These images are watermarked in order to proof its integrity; not modified by unauthorized person, and to ascertain the authenticity, that is, ensuring that the image belong to the correct patient and...
| Main Authors: | , , , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/5921/ http://irep.iium.edu.my/5921/1/05937131.pdf |
| _version_ | 1848776588370378752 |
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| author | Olanrewaju, R. F. Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha Zeki, Akram M. |
| author_facet | Olanrewaju, R. F. Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha Zeki, Akram M. |
| author_sort | Olanrewaju, R. F. |
| building | IIUM Repository |
| collection | Online Access |
| description | Medical images contain diagnostic information which
can be used for early detection of diseases. These images are watermarked in order to proof its integrity; not
modified by unauthorized person, and to ascertain the authenticity, that is, ensuring that the image belong to the correct patient and emanates from the correct source. However, the current problem with the watermarking system used for medical images is distortion introduced during the patient data/information embedding. This factor has hindered proper detection and treatment. This paper proposed a distortion free algorithm based on Fast Fourier Transform and Complex Valued Neural Network (FFT-CVNN) that can be used for watermarking medical images. The qualities of the images were evaluated with both pixel and perceptual-based metrics. Results indicate that the host image and the watermarked image were perceptually indistinguishable and the tamper detector was able to detect any form of forgery or tampering in the watermarked image. |
| first_indexed | 2025-11-14T14:32:29Z |
| format | Proceeding Paper |
| id | iium-5921 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T14:32:29Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-59212020-07-29T06:39:35Z http://irep.iium.edu.my/5921/ Detection of alterations in watermarked medical images using Fast Fourier Transform and Complex-Valued Neural Network Olanrewaju, R. F. Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha Zeki, Akram M. T Technology (General) Medical images contain diagnostic information which can be used for early detection of diseases. These images are watermarked in order to proof its integrity; not modified by unauthorized person, and to ascertain the authenticity, that is, ensuring that the image belong to the correct patient and emanates from the correct source. However, the current problem with the watermarking system used for medical images is distortion introduced during the patient data/information embedding. This factor has hindered proper detection and treatment. This paper proposed a distortion free algorithm based on Fast Fourier Transform and Complex Valued Neural Network (FFT-CVNN) that can be used for watermarking medical images. The qualities of the images were evaluated with both pixel and perceptual-based metrics. Results indicate that the host image and the watermarked image were perceptually indistinguishable and the tamper detector was able to detect any form of forgery or tampering in the watermarked image. 2011 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/5921/1/05937131.pdf Olanrewaju, R. F. and Khalifa, Othman Omran and Hassan Abdalla Hashim, Aisha and Zeki, Akram M. (2011) Detection of alterations in watermarked medical images using Fast Fourier Transform and Complex-Valued Neural Network. In: 4th International Conference on Mechatronics (ICOM 2011), 17-19 May, 2011, Kuala Lumpur, Malaysia. http://dx.doi.org/10.1109/ICOM.2011.5937131 doi:10.1109/ICOM.2011.5937131 |
| spellingShingle | T Technology (General) Olanrewaju, R. F. Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha Zeki, Akram M. Detection of alterations in watermarked medical images using Fast Fourier Transform and Complex-Valued Neural Network |
| title | Detection of alterations in watermarked medical images using Fast Fourier Transform and Complex-Valued Neural Network |
| title_full | Detection of alterations in watermarked medical images using Fast Fourier Transform and Complex-Valued Neural Network |
| title_fullStr | Detection of alterations in watermarked medical images using Fast Fourier Transform and Complex-Valued Neural Network |
| title_full_unstemmed | Detection of alterations in watermarked medical images using Fast Fourier Transform and Complex-Valued Neural Network |
| title_short | Detection of alterations in watermarked medical images using Fast Fourier Transform and Complex-Valued Neural Network |
| title_sort | detection of alterations in watermarked medical images using fast fourier transform and complex-valued neural network |
| topic | T Technology (General) |
| url | http://irep.iium.edu.my/5921/ http://irep.iium.edu.my/5921/ http://irep.iium.edu.my/5921/ http://irep.iium.edu.my/5921/1/05937131.pdf |