Image watermarking by moment invariants

Alghoniemy, Masoud; Tewfik, A.H.

doi:10.1109/icip.2000.899229

Cited by 77 publications

(40 citation statements)

References 7 publications

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“…Since the computation of discrete orthogonal moments is not involved with numerical approximation of the weight functions, while maintaining the property of orthogonal, the discrete moments are superior to traditional continuous orthogonal moments in terms of calculation accuracy and computing time. Since the discrete orthogonal moments have been introduced, they are utilized in image processing [10]- [12], pattern recognition [13], [14], and other scientific fields [15], [16]. One of the prime properties the Krawtchouk moment can provide is that it can extract features of a selected Region of Interest (ROI) in an image.…”

Section: Introductionmentioning

confidence: 99%

Local Feature Extraction Property of Krawtchouk Moment

Hu¹,

Liao²

2013

LNSE

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Abstract-Moment descriptors have long been applied in object recognition since the early years of the development of the moment theories. In recent years, the emergence of discrete orthogonal moments has substantially enriched the moment methods. In this research, we have focused our study on the local feature extraction of Krawtchouk moment and the relationship between the Region of Interest (ROI) of an image and the parameter, p, of the Krawtchouk polynomials. It has been observed that by changing parameter p of the Krawtchouk moment, the pair of reconstructed images from different orders of Krawtchouk moments with the complimentary parameters, p and 1-p, are centrosymmetric.

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Section: Introductionmentioning

confidence: 99%

Local Feature Extraction Property of Krawtchouk Moment

Hu¹,

Liao²

2013

LNSE

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“…The invariant properties under several geometric and non-geometric image distortions of many of the families made image moments an attractive transformation. Honorably, the rst work introducing the moment domain to the watermarking eld by Alghoniemy and Tewk [1] should be mentioned. They applied Hu's [9] seven moment invariants in order to detect the existence of the watermark achieving also robustness to RST (Rotation, Scale and Translation) attacks.…”

Section: Information Carriersmentioning

confidence: 99%

Should We Consider Adaptivity in Moment-based Image Watermarking ?

Papakostas¹

2014

Moments and Moment Invariants - Theory and Applications

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The term adaptivity is absent from the state-of-the-art moment-based image watermarking methods. A question to be answered is whether adaptive watermark insertion will guide to the enhancement of image's security (concerning a number of requirements such as robustness, imperceptibility, complexity and capacity). Initially, the term adaptivity is being unfold from dierent perspectives; the selection of the most qualied coecients (considering their order and magnitude) for carrying the watermark information; the selection of the most qualied image region for hosting the Efstratios D. Tsougenis

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“…Moment normalization is done mainly to resist geometrical attacks [20,21]. The normalization process of the proposed integrated method consists of two steps.…”

Section: Fig 2: Block Diagram Of Proposed Dwt-incc Approachmentioning

confidence: 99%

Integrated Normalized Content System for Efficient Watermarking

G.RoslineNesakumari¹,

Rajendran²,

Vijayakumar³

2012

IJCA

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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.

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Image watermarking by moment invariants

Cited by 77 publications

References 7 publications

Local Feature Extraction Property of Krawtchouk Moment

Local Feature Extraction Property of Krawtchouk Moment

Should We Consider Adaptivity in Moment-based Image Watermarking ?

Integrated Normalized Content System for Efficient Watermarking

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