Geometric modelling of the wavelet coefficients for image watermarking using optimum detector

Hamghalam, Mohammad; Mirzakuchaki, Sattar; Akhaee, Mohammad Ali

doi:10.1049/iet-ipr.2013.0386

Cited by 29 publications

(10 citation statements)

References 34 publications

(60 reference statements)

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“…If the value of (2) is greater than a pre-determined threshold, then the watermark is said to be present. The threshold depends on the chosen false positive probability [15]. SS watermarking was shown to be efficient, robust, and cryptographically secured.…”

Section: Models Of Quantization and Ss Watermarkingmentioning

confidence: 99%

“…According to the previous works [13,15], a few observations are in order about the given method. The embedding capacity is closely related to the quantization step , the signal size L , and the utilized coding technique.…”

Section: Dual Watermarking Modelmentioning

confidence: 99%

“…In the experiment, the watermarked images first undergo a certain attack and then the watermark detection is performed on the nonwatermarked images and the attacked images. The detection performance is measured by the receiver operating characteristics (ROC), which describes the relation between PFA and the probability of miss detection (PMD) under different values of the decision threshold [15]. In Fig.…”

Section: Watermark Robustnessmentioning

confidence: 99%

See 2 more Smart Citations

Optimal watermark embedding combining spread spectrum and quantization

Zhu

Sun

Meng

et al. 2016

EURASIP J. Adv. Signal Process.

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This paper presents an optimal watermark embedding method combining spread spectrum and quantization. In the method, the host signal vector is quantized to embed a multiple-bit watermark, and meanwhile, the quantized signal is made to locate in the detectable region defined in the context of spread spectrum watermarking. Under the two constraints, the optimal watermarked signal is derived in the sense of minimizing the embedding distortion. The proposed method is further implemented in wavelet transform domain, where the insensitive wavelet coefficients are selected according to the modified human visual model for watermark embedding. Simulations on real images by using the wavelet-based implementations demonstrate the proposed method performs very well in both watermark imperceptibility and robustness and is more robust to typical signal processes, e.g., additive noise, JPEG compression, etc., as compared with the state-of-the-art watermarking methods.

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Section: Models Of Quantization and Ss Watermarkingmentioning

confidence: 99%

Section: Dual Watermarking Modelmentioning

confidence: 99%

Section: Watermark Robustnessmentioning

confidence: 99%

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Optimal watermark embedding combining spread spectrum and quantization

Zhu

Sun

Meng

et al. 2016

EURASIP J. Adv. Signal Process.

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“…Spatial domain methods are usually less susceptible to conventional image processing attacks because the information is directly embedded in image pixels and easily manipulated. There are various techniques in the transform domain such as Discrete Cosine Transform (DCT) [3]- [5], Fourier Discrete Transform (DFT), Discrete Wavelet Transform (DWT) [6]- [8], Contourlet Transform (CT) and Hadamard Conversion [2]. In [3], authors introduce an adaptive blind watermarking in which the watermark is embedded in DCT coefficients of CT. Two-level CT is applied to the host image.…”

Section: Introductionmentioning

confidence: 99%

Robustness and Imperceptibility Enhancement in Watermarked Images by Color Transformation

Jamali

Bagheri

Karimi

et al. 2020

2020 25th International Computer Conference, Computer Society of Iran (CSICC)

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One of the effective methods for the preservation of copyright ownership of digital media is watermarking. Different watermarking techniques try to set a tradeoff between robustness and transparency of the process. In this research work, we have used color space conversion and frequency transform to achieve high robustness and transparency. Due to the distribution of image information in the RGB domain, we use YUV color space, which concentrates the visual information in the Y channel. Embedding of the watermark is performed in the DCT coefficients of the specific wavelet subbands. Experimental results show high transparency and robustness of the proposed method.

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“…RELATED WORKS The ISC technology using steganography process conducts itself with hidden data or image. Several authors has proposed steganography or digital watermarking techniques to solve the problems associated by geometric transformation [6], [7].…”

Section: Introductionmentioning

confidence: 99%

Mathematical modeling for calibrating illuminated image in image sensor communication

Hossain

Hong

Ifthekhar

et al. 2015

2015 International Conference on Information and Communication Technology Convergence (ICTC)

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Image sensor communication (ISC) has become more imperative for the technology lover by virtue of the development of image sensors in the camera. Lately, Digital signage technology has become one of the most flourished industry for ISC technology as it has uncovered a lot of opportunities such as interactivity, dynamic content provisioning and so on. Granting all this opportuneness, there are some major issues in the case of ISC technology when the communication system specifies the communication by means of steganography process (Inserting data in the video image). Geometric and photometric transformations of the image are among them while the display and the camera act as a transmitter and a receiver in ISC, respectively. Due to this effect, the data can be changed or noise can be even more influential than the required signal. To achieve a relevant communication method, the influence of these transformational issues need to be taken into care. We proposed a mathematical modeling to figure out the photometric effects created by illumination from the light source of the environment in this paper. The channel model is used as non-Lambertian model. The novelty of this work implies the unification of computer vision and proposed channel model to remove the photometric transformational effects due to illumination in an image.

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Geometric modelling of the wavelet coefficients for image watermarking using optimum detector

Cited by 29 publications

References 34 publications

Optimal watermark embedding combining spread spectrum and quantization

Optimal watermark embedding combining spread spectrum and quantization

Robustness and Imperceptibility Enhancement in Watermarked Images by Color Transformation

Mathematical modeling for calibrating illuminated image in image sensor communication

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