Joint robustness and security enhancement for feature-based image watermarking using invariant feature regions

Tsai, Jen-Sheng; Huang, Win-Bin; Kuo, Yau‐Hwang; Horng, Mong-Fong

doi:10.1016/j.sigpro.2011.11.033

Cited by 54 publications

(19 citation statements)

References 38 publications

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“…The secret leakage is controlled by identifying the local image features with the help of this technique. Given an input image, the scale space I is calculated using the function L at a set of scales that represent various levels of resolution [15]. It is defined with…”

Section: A Detection Of Image Featuresmentioning

confidence: 99%

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Enhancement of robustness and security for feature-based watermarking using wavelets

Akila¹,

Sumathi²

2014

2014 International Conference on Recent Trends in Information Technology

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Generally, feature-based image watermarking uses the local image features present in an image. The invariance of the features is exploited for achieving robustness against attacks, but the leakage of information is often unconsidered. Here an image adaptive watermarking approach is proposed which uses invariant feature regions for enhancing the robustness and security. Feature regions are determined using the scale-adapted auto correlation matrix and the Laplacian-ofGaussian operation. The leakage of the information can be controlled with the feature detection procedure. Circular feature regions are determined due to its invariance property. The selected regions are normalized to obtain a geometrically invariant feature region into which the watermark is embedded with the hybrid DWT-SVD algorithm. The evaluation results present the proposed scheme can withstand various attacks which may also include the noise attacks, signal processing attacks and geometric distortion. This results in the enhancement of the robustness.

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Section: A Detection Of Image Featuresmentioning

confidence: 99%

“…From a set of scale levels, the candidate points can be achieved. Depending upon the applications, the number of scale levels n σ varies which relies on the changes made on the scale of image and here it is set to 15 [15]. On obtaining the points the circular feature region is determined by following equation…”

Section: A Detection Of Image Featuresmentioning

confidence: 99%

Enhancement of robustness and security for feature-based watermarking using wavelets

Akila¹,

Sumathi²

2014

2014 International Conference on Recent Trends in Information Technology

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“…Mayank et al [37] presented a 3-level RDWT biometric watermarking algorithm to embed the voice biometric MFC coefficients in a color face image of the same individual for increased robustness, security and accuracy. Tsai et al [35] propose a novel image watermarking approach, which adopts invariant feature regions to jointly enhance its robustness and security. Initially, circular feature regions are determined by the scale-adapted auto-correlation matrix and the Laplacian-of-Gaussian operation.…”

Section: Background Of Localized Watermarkingmentioning

confidence: 99%

Bayesian Segmentation Based Local Geometrically Invariant Image Watermarking

Wang

Yang

Wang

et al. 2013

Fundamenta Informaticae

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Robust digital watermarking has been an active research topic in the last decade. As one of the promising approaches, feature point based image watermarking has attracted many researchers. However, the related work usually suffers from the following limitations: 1) The feature point detector is sensitive to texture region, and some noise feature points are always detected in the texture region. 2) The feature points focus too much on high contrast region, and the feature points are distributed unevenly. Based on Bayesian image segmentation, we propose a local geometrically invariant image watermarking scheme with good visual quality in this paper. Firstly, the Bayesian image segmentation is used to segment the host image into several homogeneous regions. Secondly, for each homogeneous region, image feature points are extracted using the multiscale Harris-Laplace detector, and the corresponding invariant local image regions are constructed adaptively. Finally, by taking the human visual system (HVS) into account, digital watermark is repeatedly embedded into local image regions by modulating the magnitudes of DFT coefficients. By binding the digital watermark with the invariant local image regions, the watermark detection can be done without synchronization error. Experimental results show that the proposed image watermarking is not only invisible and robust against common image processing operations such as sharpening, noise adding, and JPEG compression etc, but also robust against the geometric distortions.

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“…However, these schemes are vulnerable to attacks, especially when the watermarked image is attacked with geometric attacks. To resist geometric attacks against medical image watermark, some schemes applied to natural images can be used as reference [7][8][9]. However, these schemes could not be used in medical image watermarking either because of the low embedding capacity or the unacceptable perceptional quality.…”

Section: Introductionmentioning

confidence: 99%

Robust Medical Image Watermarking Scheme with Rotation Correction

Lin

Gao

Sheng

et al. 2014

Advances in Intelligent Systems and Computing

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Abstract. In order to protect the image contents, many reversible medical image watermarking schemes have been proposed, although reversibility guaranteed the lossless of the cover image, but it also has some shortcomings such as it is vulnerable to geometrical attacks. So a novel robust watermarking scheme for medical image based on the combination Redundancy Discrete Wavelet Transform (RDWT) and Singular Value Decomposition (SVD) is proposed in this letter. Different from the reversibility, which guarantees the perceptional lossless, the proposed scheme achieves satisfied visual quality by exploiting the visually masking property of RDWT, in the meantime, Speeded-Up Robust Features (SURF) and Random sample consensus (RANSAC) based rotation correction scheme is put forward, which can be used to restore the attacked image to the original state. The experimental results show that the proposed scheme has the large amounts of embedding capacity; it is also robust against rotation attacks; and the perceptional quality of watermarked image meets the need of usage in medical images.

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Joint robustness and security enhancement for feature-based image watermarking using invariant feature regions

Cited by 54 publications

References 38 publications

Enhancement of robustness and security for feature-based watermarking using wavelets

Enhancement of robustness and security for feature-based watermarking using wavelets

Bayesian Segmentation Based Local Geometrically Invariant Image Watermarking

Robust Medical Image Watermarking Scheme with Rotation Correction

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