Distortion-Free Digital Watermarking for Medical Images (Fundus) using Complex- Valued Neural Network
Fundus image is the interior surface of the eye that includes the optic nerves, macula and retinal blood vessels. The optic nerve which is responsible for transmitting of electrical impulses from the retina to the brain is connected to the back of the eye near the macula has a visible portion of the...
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| Format: | Monograph |
| Language: | English |
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IIUM
2015
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| Online Access: | http://irep.iium.edu.my/46160/ http://irep.iium.edu.my/46160/1/Full_version_of_ReserachReport_CVNN_ver__December_3.pdf |
| _version_ | 1848782919132250112 |
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| author | Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha Olanrewaju, Rashidah Funke |
| author_facet | Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha Olanrewaju, Rashidah Funke |
| author_sort | Khalifa, Othman Omran |
| building | IIUM Repository |
| collection | Online Access |
| description | Fundus image is the interior surface of the eye that includes the optic nerves, macula and retinal blood vessels. The optic nerve which is responsible for transmitting of electrical impulses from the retina to the brain is connected to the back of the eye near the macula has a visible portion of the optic nerve called the optic disc. Optic disk has been shown to provide diagnostic information related to diabetic retinopathy (DR) and glaucoma diseases. Since such image are used for early detection of numbers of ocular disease which still remain the legal cause of blindness in working age population. Protection and authentication of such medical images are now becoming increasingly important in an e-Health environment. Though several high-ranking watermarking schemes using neural networks have been proposed in order to make watermark stronger in protection of medical images to resist attacks. However, the current system only deals with real value data. Once the data become complex, the current algorithms are not capable of handling complex data. In this study, a distortion-free digital watermarking scheme based on Complex-Valued Neural Network (CVNN) in transform domain is proposed. Fast Fourier Transform (FFT) was used to obtain the complex number (real and imaginary part) of the host image. The complex values form the input data of the Complex Back-Propagation (CBP) algorithm. Because neural networks perform best on detection, classification, learning and adaption, these features are employed to simulate the Safe Region (SR) to embed the watermark, thus, watermark are appropriately mapped to the mid frequency of selected coefficients. The algorithm was appraised by Mean Squared Error MSE and Average Difference Indicator (ADI). Implementation results have shown that this watermarking algorithm has a high level of robustness and accuracy in recovery of the watermark. |
| first_indexed | 2025-11-14T16:13:06Z |
| format | Monograph |
| id | iium-46160 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T16:13:06Z |
| publishDate | 2015 |
| publisher | IIUM |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-461602023-11-17T04:15:00Z http://irep.iium.edu.my/46160/ Distortion-Free Digital Watermarking for Medical Images (Fundus) using Complex- Valued Neural Network Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha Olanrewaju, Rashidah Funke TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices TK7885 Computer engineering Fundus image is the interior surface of the eye that includes the optic nerves, macula and retinal blood vessels. The optic nerve which is responsible for transmitting of electrical impulses from the retina to the brain is connected to the back of the eye near the macula has a visible portion of the optic nerve called the optic disc. Optic disk has been shown to provide diagnostic information related to diabetic retinopathy (DR) and glaucoma diseases. Since such image are used for early detection of numbers of ocular disease which still remain the legal cause of blindness in working age population. Protection and authentication of such medical images are now becoming increasingly important in an e-Health environment. Though several high-ranking watermarking schemes using neural networks have been proposed in order to make watermark stronger in protection of medical images to resist attacks. However, the current system only deals with real value data. Once the data become complex, the current algorithms are not capable of handling complex data. In this study, a distortion-free digital watermarking scheme based on Complex-Valued Neural Network (CVNN) in transform domain is proposed. Fast Fourier Transform (FFT) was used to obtain the complex number (real and imaginary part) of the host image. The complex values form the input data of the Complex Back-Propagation (CBP) algorithm. Because neural networks perform best on detection, classification, learning and adaption, these features are employed to simulate the Safe Region (SR) to embed the watermark, thus, watermark are appropriately mapped to the mid frequency of selected coefficients. The algorithm was appraised by Mean Squared Error MSE and Average Difference Indicator (ADI). Implementation results have shown that this watermarking algorithm has a high level of robustness and accuracy in recovery of the watermark. IIUM 2015 Monograph NonPeerReviewed application/pdf en http://irep.iium.edu.my/46160/1/Full_version_of_ReserachReport_CVNN_ver__December_3.pdf Khalifa, Othman Omran and Hassan Abdalla Hashim, Aisha and Olanrewaju, Rashidah Funke (2015) Distortion-Free Digital Watermarking for Medical Images (Fundus) using Complex- Valued Neural Network. UNSPECIFIED. IIUM. (Unpublished) |
| spellingShingle | TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices TK7885 Computer engineering Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha Olanrewaju, Rashidah Funke Distortion-Free Digital Watermarking for Medical Images (Fundus) using Complex- Valued Neural Network |
| title | Distortion-Free Digital Watermarking for Medical Images (Fundus) using Complex- Valued Neural Network |
| title_full | Distortion-Free Digital Watermarking for Medical Images (Fundus) using Complex- Valued Neural Network |
| title_fullStr | Distortion-Free Digital Watermarking for Medical Images (Fundus) using Complex- Valued Neural Network |
| title_full_unstemmed | Distortion-Free Digital Watermarking for Medical Images (Fundus) using Complex- Valued Neural Network |
| title_short | Distortion-Free Digital Watermarking for Medical Images (Fundus) using Complex- Valued Neural Network |
| title_sort | distortion-free digital watermarking for medical images (fundus) using complex- valued neural network |
| topic | TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices TK7885 Computer engineering |
| url | http://irep.iium.edu.my/46160/ http://irep.iium.edu.my/46160/1/Full_version_of_ReserachReport_CVNN_ver__December_3.pdf |