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Invariant domain watermarking using heaviside function of order alpha and fractional Gaussian field.

Abbasi A, Woo CS, Ibrahim RW, Islam S - PLoS ONE (2015)

Bottom Line: A cross correlation method based on the fractional Gaussian field is used for watermark detection.Furthermore the proposed method enables blind watermark detection where the original image is not required during the watermark detection thereby making it more practical than non-blind watermarking techniques.Experimental results confirmed that the proposed technique has a high level of robustness.

View Article: PubMed Central - PubMed

Affiliation: Department of Artificial Intelligence, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia.

ABSTRACT
Digital image watermarking is an important technique for the authentication of multimedia content and copyright protection. Conventional digital image watermarking techniques are often vulnerable to geometric distortions such as Rotation, Scaling, and Translation (RST). These distortions desynchronize the watermark information embedded in an image and thus disable watermark detection. To solve this problem, we propose an RST invariant domain watermarking technique based on fractional calculus. We have constructed a domain using Heaviside function of order alpha (HFOA). The HFOA models the signal as a polynomial for watermark embedding. The watermark is embedded in all the coefficients of the image. We have also constructed a fractional variance formula using fractional Gaussian field. A cross correlation method based on the fractional Gaussian field is used for watermark detection. Furthermore the proposed method enables blind watermark detection where the original image is not required during the watermark detection thereby making it more practical than non-blind watermarking techniques. Experimental results confirmed that the proposed technique has a high level of robustness.

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Watermark Detection.
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pone.0123427.g003: Watermark Detection.

Mentions: Watermark detection is the reverse of the embedding processes and it is shown in Fig 3. Our aim is to extract the watermark using fractional Gaussian field [6]. The fractional Gaussian field has a simple covariance structure and it is related to two generalizations of fractional motion known as multifunction motions. The Gaussian field due to its inherent duality reveals a new way of constructing martingales associated with the odd and even parts of a fractional motion.


Invariant domain watermarking using heaviside function of order alpha and fractional Gaussian field.

Abbasi A, Woo CS, Ibrahim RW, Islam S - PLoS ONE (2015)

Watermark Detection.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4401616&req=5

pone.0123427.g003: Watermark Detection.
Mentions: Watermark detection is the reverse of the embedding processes and it is shown in Fig 3. Our aim is to extract the watermark using fractional Gaussian field [6]. The fractional Gaussian field has a simple covariance structure and it is related to two generalizations of fractional motion known as multifunction motions. The Gaussian field due to its inherent duality reveals a new way of constructing martingales associated with the odd and even parts of a fractional motion.

Bottom Line: A cross correlation method based on the fractional Gaussian field is used for watermark detection.Furthermore the proposed method enables blind watermark detection where the original image is not required during the watermark detection thereby making it more practical than non-blind watermarking techniques.Experimental results confirmed that the proposed technique has a high level of robustness.

View Article: PubMed Central - PubMed

Affiliation: Department of Artificial Intelligence, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia.

ABSTRACT
Digital image watermarking is an important technique for the authentication of multimedia content and copyright protection. Conventional digital image watermarking techniques are often vulnerable to geometric distortions such as Rotation, Scaling, and Translation (RST). These distortions desynchronize the watermark information embedded in an image and thus disable watermark detection. To solve this problem, we propose an RST invariant domain watermarking technique based on fractional calculus. We have constructed a domain using Heaviside function of order alpha (HFOA). The HFOA models the signal as a polynomial for watermark embedding. The watermark is embedded in all the coefficients of the image. We have also constructed a fractional variance formula using fractional Gaussian field. A cross correlation method based on the fractional Gaussian field is used for watermark detection. Furthermore the proposed method enables blind watermark detection where the original image is not required during the watermark detection thereby making it more practical than non-blind watermarking techniques. Experimental results confirmed that the proposed technique has a high level of robustness.

Show MeSH
Related in: MedlinePlus