Computational intelligence: application in digital watermarking

Impersonation and piracy of intellectual properties remain an indispensable problem across the globe. Currently over millions of digital songs, images and videos are copied illegally during file-sharing over the networks, costing loss of revenue to multimedia industries. Digital Watermarking (DW)...

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Main Authors:	Olanweraju, Rashidah Funke, Khalifa, Othman Omran
Format:	Conference or Workshop Item
Language:	English
Published:	2012
Subjects:	QA Mathematics
Online Access:	http://irep.iium.edu.my/24627/ http://irep.iium.edu.my/24627/1/2076C.pdf

id	iium-24627
recordtype	eprints
spelling	iium-246272012-12-18T02:33:14Z http://irep.iium.edu.my/24627/ Computational intelligence: application in digital watermarking Olanweraju, Rashidah Funke Khalifa, Othman Omran QA Mathematics Impersonation and piracy of intellectual properties remain an indispensable problem across the globe. Currently over millions of digital songs, images and videos are copied illegally during file-sharing over the networks, costing loss of revenue to multimedia industries. Digital Watermarking (DW) is an efficient method that embeds an imperceptible message in digital object to protect copyright and authenticate digital media in order to prevent forgery and impersonation. Computational Intelligence (CI); a well-established paradigm is currently gaining attraction in the field of information hiding due to its ability to solve and improve complex problems encountered. CI has been applied in digital watermarking to improve performance in order to curb piracy. This paper brings to view computational intelligence techniques specifically the Artificial Neural Network (ANN); generalizations of mathematical models based on biological nervous systems and its applications in digital watermarking. Mathematical model of ANN in relation to digital watermarking is indentified, elucidated and simplified. Results of image watermarking using both ANN and no ANN were compared. Embedding using NN showed the optimum imperceptibility result as well as enhancement in robustness of the system before and after attacks; IFM equal to 0.9588 of 1.0000 was obtained using NN to embed, meaning that there was almost no loss of fidelity in the watermarked image. It is anticipated that this paper will serve as a launch pad for researchers interested in intelligent watermarking. 2012-07-04 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/24627/1/2076C.pdf Olanweraju, Rashidah Funke and Khalifa, Othman Omran (2012) Computational intelligence: application in digital watermarking. In: 2nd International Conference on Mathematical Applications in Engineering (ICMAE2012), 3 - 5 July 2012, Seri Pacific Hotel Kuala Lumpur, Malaysia.
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	QA Mathematics
spellingShingle	QA Mathematics Olanweraju, Rashidah Funke Khalifa, Othman Omran Computational intelligence: application in digital watermarking
description	Impersonation and piracy of intellectual properties remain an indispensable problem across the globe. Currently over millions of digital songs, images and videos are copied illegally during file-sharing over the networks, costing loss of revenue to multimedia industries. Digital Watermarking (DW) is an efficient method that embeds an imperceptible message in digital object to protect copyright and authenticate digital media in order to prevent forgery and impersonation. Computational Intelligence (CI); a well-established paradigm is currently gaining attraction in the field of information hiding due to its ability to solve and improve complex problems encountered. CI has been applied in digital watermarking to improve performance in order to curb piracy. This paper brings to view computational intelligence techniques specifically the Artificial Neural Network (ANN); generalizations of mathematical models based on biological nervous systems and its applications in digital watermarking. Mathematical model of ANN in relation to digital watermarking is indentified, elucidated and simplified. Results of image watermarking using both ANN and no ANN were compared. Embedding using NN showed the optimum imperceptibility result as well as enhancement in robustness of the system before and after attacks; IFM equal to 0.9588 of 1.0000 was obtained using NN to embed, meaning that there was almost no loss of fidelity in the watermarked image. It is anticipated that this paper will serve as a launch pad for researchers interested in intelligent watermarking.
format	Conference or Workshop Item
author	Olanweraju, Rashidah Funke Khalifa, Othman Omran
author_facet	Olanweraju, Rashidah Funke Khalifa, Othman Omran
author_sort	Olanweraju, Rashidah Funke
title	Computational intelligence: application in digital watermarking
title_short	Computational intelligence: application in digital watermarking
title_full	Computational intelligence: application in digital watermarking
title_fullStr	Computational intelligence: application in digital watermarking
title_full_unstemmed	Computational intelligence: application in digital watermarking
title_sort	computational intelligence: application in digital watermarking
publishDate	2012
url	http://irep.iium.edu.my/24627/ http://irep.iium.edu.my/24627/1/2076C.pdf
first_indexed	2023-09-18T20:36:55Z
last_indexed	2023-09-18T20:36:55Z
_version_	1777409107537428480

Computational intelligence: application in digital watermarking

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