Geometric Invariance in Image Watermarking

Alghoniemy, Masoud; Tewfik, A.H.

doi:10.1109/tip.2004.823831

Cited by 220 publications

(88 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This imaging process creates both photometric and geometric distortions in the observed image. Many robust invariant watermark methods are designed for geometric distortions including invariant moments [1,7,12], normalization methods [6], fractal methods [19] and invariant features [21,23]. Our method handles both geometric and photometric distortions by applying appropriate computer vision methods.…”

Section: Related Workmentioning

confidence: 99%

Dynamic and invisible messaging for visual MIMO

Yuan

Dana

Ashok

et al. 2012

2012 IEEE Workshop on the Applications of Computer Vision (WACV)

View full text Add to dashboard Cite

show abstract

Section: Related Workmentioning

confidence: 99%

Dynamic and invisible messaging for visual MIMO

Yuan

Dana

Ashok

et al. 2012

2012 IEEE Workshop on the Applications of Computer Vision (WACV)

View full text Add to dashboard Cite

show abstract

“…It also helps researchers to achieve scaling invariance in watermarking domain [19]. Geometric moments are used for normalizing the image geometrically before watermark embedding at the encoder and before extracting the watermark at the decoder.…”

Section: Watermark Embedding Process Stage One -Image Normalization Wmentioning

confidence: 99%

Integrated Normalized Content System for Efficient Watermarking

G.RoslineNesakumari¹,

Rajendran²,

Vijayakumar³

2012

IJCA

View full text Add to dashboard Cite

In contemporary years, different watermarking schemes are proposed for image authentication and copyright protection. In images, any tiny change to the content is not acceptable; the embedding distortion has to be compensated for perfectly. In this paper a powerful Image watermarking method using DWT based on integrated normalized content based chaotic (DWT-INCC) system is proposed, to obtain better digital content authentication, originality, higher embedding capacity, quality of the information and better robustness. The objective of the proposed integrated scheme is to examine how content image normalization and discrete wavelet domain based chaotic system procedure are used to enhance robustness of a digital image watermark especially for statistical attacks. The proposed integrated scheme consists of four stages. In the stage two image normalization is performed, to achieve the scaling and rotational invariance. In stage two DWT is applied on the normalized image. In stage three a block based content authentication scheme is adopted on the normalized image of stage one for image authentication and tamper localization. In stage four chaotic models is adopted on the stage three to achieve excellent robustness against any statistical attacks and to increase the security of the digital watermarking system. The experimental result shows that the proposed DWT-INCC method is more robust and effective even in the presence of various attacks when compared with many existing methods.

show abstract

“…Li et al (2003) proposed a watermarking method in which the rotation angle and scaling factor are estimated after the watermarked image has been scaled or/and rotated by using geometric moments of original image. Alghoniemy and Tewfik (2004) embed the watermark by modifying the moment values of the image in a way such that a predefined function of the moment invariants lies within a predetermined value.…”

Section: Introductionmentioning

confidence: 99%

Invariant Image Watermarking Using Accurate Zernike Moments

Ismail¹,

Shouman²,

Hosny³

et al. 2010

Journal of Computer Science

View full text Add to dashboard Cite

problem statement: Digital image watermarking is the most popular method for image authentication, copyright protection and content description. Zernike moments are the most widely used moments in image processing and pattern recognition. The magnitudes of Zernike moments are rotation invariant so they can be used just as a watermark signal or be further modified to carry embedded data. The computed Zernike moments in Cartesian coordinate are not accurate due to geometrical and numerical error. Approach: In this study, we employed a robust image-watermarking algorithm using accurate Zernike moments. These moments are computed in polar coordinate, where both approximation and geometric errors are removed. Accurate Zernike moments are used in image watermarking and proved to be robust against different kind of geometric attacks. The performance of the proposed algorithm is evaluated using standard images. Results: Experimental results show that, accurate Zernike moments achieve higher degree of robustness than those approximated ones against rotation, scaling, flipping, JPEG compression and affine transformation. Conclusion: By computing accurate Zernike moments, the embedded bits watermark can be extracted at low error rate.

show abstract

Geometric Invariance in Image Watermarking

Cited by 220 publications

References 20 publications

Dynamic and invisible messaging for visual MIMO

Dynamic and invisible messaging for visual MIMO

Integrated Normalized Content System for Efficient Watermarking

Invariant Image Watermarking Using Accurate Zernike Moments

Contact Info

Product

Resources

About