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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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Robustness of Proposed Technique against Cropping attack.(a-c) Original images of size 512×512 pixels. (d) strips 25 and 26 pixels wide were cropped from the bottom and right hand side of the image respectively. The size of the image after cropping attack is 487×486 pixels. (e) strips 54 pixels wide were cropped from the bottom and right hand side of the image. The size of the image after cropping attack is 458×458 pixels. (f) strips 149 pixels wide were cropped from the bottom and right hand side of the image. The size of the image after cropping attack is 363×363 pixels.
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pone.0123427.g010: Robustness of Proposed Technique against Cropping attack.(a-c) Original images of size 512×512 pixels. (d) strips 25 and 26 pixels wide were cropped from the bottom and right hand side of the image respectively. The size of the image after cropping attack is 487×486 pixels. (e) strips 54 pixels wide were cropped from the bottom and right hand side of the image. The size of the image after cropping attack is 458×458 pixels. (f) strips 149 pixels wide were cropped from the bottom and right hand side of the image. The size of the image after cropping attack is 363×363 pixels.

Mentions: Robustness of the proposed technique against JPEG compression attack with quality factor ranging from 10 to 90 were tested. Fig 4 represent the comparison of correlation value against the threshold value, after the JPEG attack. The result confirms that the proposed technique is robust against the JPEG compression attack. Further we evaluated the performance of the proposed technique under different attacks and the results are summarized in Figs 5–10. The cross correlation computation based on fractional Gaussian field criterion ρ and the threshold value Tρ are considered to test the presence of the embedded watermark.


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

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

Robustness of Proposed Technique against Cropping attack.(a-c) Original images of size 512×512 pixels. (d) strips 25 and 26 pixels wide were cropped from the bottom and right hand side of the image respectively. The size of the image after cropping attack is 487×486 pixels. (e) strips 54 pixels wide were cropped from the bottom and right hand side of the image. The size of the image after cropping attack is 458×458 pixels. (f) strips 149 pixels wide were cropped from the bottom and right hand side of the image. The size of the image after cropping attack is 363×363 pixels.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0123427.g010: Robustness of Proposed Technique against Cropping attack.(a-c) Original images of size 512×512 pixels. (d) strips 25 and 26 pixels wide were cropped from the bottom and right hand side of the image respectively. The size of the image after cropping attack is 487×486 pixels. (e) strips 54 pixels wide were cropped from the bottom and right hand side of the image. The size of the image after cropping attack is 458×458 pixels. (f) strips 149 pixels wide were cropped from the bottom and right hand side of the image. The size of the image after cropping attack is 363×363 pixels.
Mentions: Robustness of the proposed technique against JPEG compression attack with quality factor ranging from 10 to 90 were tested. Fig 4 represent the comparison of correlation value against the threshold value, after the JPEG attack. The result confirms that the proposed technique is robust against the JPEG compression attack. Further we evaluated the performance of the proposed technique under different attacks and the results are summarized in Figs 5–10. The cross correlation computation based on fractional Gaussian field criterion ρ and the threshold value Tρ are considered to test the presence of the embedded watermark.

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