Damageless digital watermarking using complex-valued artificial neural network

Several high-ranking watermarking schemes using neural networks have been proposed in order to make the watermark stronger 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....

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Main Authors:	Olanweraju, Rashidah Funke, Ali Aburas, Abdurazzag, Khalifa, Othman Omran, Hassan Abdalla Hashim, Aisha
Format:	Article
Language:	English
Published:	UUM Press 2010
Subjects:	QA75 Electronic computers. Computer science T Technology (General)
Online Access:	http://irep.iium.edu.my/5612/ http://irep.iium.edu.my/5612/ http://irep.iium.edu.my/5612/1/DAMAGELESS_DIGITAL_WATERMARKING_USING_COMPLEXVALUED.pdf

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spelling	iium-56122012-12-13T05:17:52Z http://irep.iium.edu.my/5612/ Damageless digital watermarking using complex-valued artificial neural network Olanweraju, Rashidah Funke Ali Aburas, Abdurazzag Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha QA75 Electronic computers. Computer science T Technology (General) Several high-ranking watermarking schemes using neural networks have been proposed in order to make the watermark stronger 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 paper, 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 coeffi cients. 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. UUM Press 2010 Article PeerReviewed application/pdf en http://irep.iium.edu.my/5612/1/DAMAGELESS_DIGITAL_WATERMARKING_USING_COMPLEXVALUED.pdf Olanweraju, Rashidah Funke and Ali Aburas, Abdurazzag and Khalifa, Othman Omran and Hassan Abdalla Hashim, Aisha (2010) Damageless digital watermarking using complex-valued artificial neural network. Journal of Information and Communication Technology, 9. pp. 111-137. ISSN 2180-3862 (O), 1675-414X (P) http://jict.uum.edu.my/index.php?option=com_phocadownload&view=category&id=12&Itemid=11
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	QA75 Electronic computers. Computer science T Technology (General)
spellingShingle	QA75 Electronic computers. Computer science T Technology (General) Olanweraju, Rashidah Funke Ali Aburas, Abdurazzag Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha Damageless digital watermarking using complex-valued artificial neural network
description	Several high-ranking watermarking schemes using neural networks have been proposed in order to make the watermark stronger 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 paper, 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 coeffi cients. 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.
format	Article
author	Olanweraju, Rashidah Funke Ali Aburas, Abdurazzag Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha
author_facet	Olanweraju, Rashidah Funke Ali Aburas, Abdurazzag Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha
author_sort	Olanweraju, Rashidah Funke
title	Damageless digital watermarking using complex-valued artificial neural network
title_short	Damageless digital watermarking using complex-valued artificial neural network
title_full	Damageless digital watermarking using complex-valued artificial neural network
title_fullStr	Damageless digital watermarking using complex-valued artificial neural network
title_full_unstemmed	Damageless digital watermarking using complex-valued artificial neural network
title_sort	damageless digital watermarking using complex-valued artificial neural network
publisher	UUM Press
publishDate	2010
url	http://irep.iium.edu.my/5612/ http://irep.iium.edu.my/5612/ http://irep.iium.edu.my/5612/1/DAMAGELESS_DIGITAL_WATERMARKING_USING_COMPLEXVALUED.pdf
first_indexed	2023-09-18T20:14:18Z
last_indexed	2023-09-18T20:14:18Z
_version_	1777407684024205312

Damageless digital watermarking using complex-valued artificial neural network

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