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Different types of digital watermarking. The type of watermark used in this work is denoted by the grey rectangles.
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The multimedia revolution has made a strong impact on our society. The explosive growth of Internet access to this digital information has generated new opportunities and challenges. The ease of editing and duplicating information in the digital domain has created copyright protection concerns for content providers. Various schemes to embed seconda...
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... upon the application requirements, one can employ different types of watermarking. Figure 1 shows a general classification of watermarking. Each of these watermarking schemes has its own applications and usefulness [1,2,3]. ...
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... is more robust with respect to noise. As mentioned, from Tables 2, 3, and 4, the average PSNR value for the "Pepper" image is maximum, 53.80 dB. Similarly, the minimum value for average PSNR is for the "Bear" image, which is 45.14 dB. The graphs of PSNR versus α, RMSE versus α, and SSIM versus α for the "Pepper" and "Bear" images are shown in Fig. (17(a)), (17(b)), (18(a)), (18(b)), ...
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... compression is a widely used algorithm for image compression and is considered an unintentional attack. Various Quality Factors (QF = 75%, 50%, 25% and 10%) are used to compress the watermarked image (shown only for the "Bear" image), and the resulting images are shown in Figs. (21(a)), (21(b)), and (21(c)). The resulting images are then tested for watermark extraction, and Table (6) shows the results. The results show that if higher values of α are used for embedding, then the watermark can resist higher levels of JPEG compression. ...
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... insertion unit is composed of several sub-modules: a DCT module, a perceptual ana- lyzer, a scale factor, and the insertion module. The DCT module calculates the DCT co- efficients of the host image. The controller manages the operation schedules of all other modules and the data flow of the unit. Fig. (31) illustrates the watermark insertion ...
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Citations
... Three pairs of DCT coefficients were selected on each DCT block. The selected three pairs of DCT coefficients B (7,2) , B (6,3) , B (3,6) , B (2,7) , B (6,7) , B (7,6) were located in the high frequency. The selected coefficient pairs are positioned diagonally and the embedding watermark bits into the selected DCT coefficients uses a fixed threshold. ...
... Three pairs of DCT coefficients were selected on each DCT block. The selected three pairs of DCT coefficients B (7,2) , B (6,3) , B (3,6) , B (2,7) , B (6,7) , B (7,6) were located in the high frequency. The selected coefficient pairs are positioned diagonally and the embedding watermark bits into the selected DCT coefficients uses a fixed threshold. ...
... Three pairs of DCT coefficients were selected on each DCT block. The selected three pairs of DCT coefficients B (7,2) , B (6,3) , B (3,6) , B (2,7) , B (6,7) , B (7,6) were located in the high frequency. The selected coefficient pairs are positioned diagonally and the embedding watermark bits into the selected DCT coefficients uses a fixed threshold. ...
This survey presented a discussion of the existing scaling factor and adaptive scaling factor in image watermarking schemes. The discussion included several issues: robustness, imperceptibility and computational time for embedding a watermark. This survey also discussed the general concept of the image watermarking, transform method, embedding region and security on the existing watermarking scheme. This paper also discussed the recent use of watermarking techniques, potential issues and available solutions in adaptive watermarking schemes. Furthermore, the performance summary of the state-of-art embedding techniques is presented and analysed for future research. This literature review became useful to researchers to know the current challenges in embedding a watermark image. This survey information can be used to design an efficient embedding watermark for copyright protection.
... The authors of [27] propose a blind RGB images watermarking technique which employs a 3D Henon chaotic map in conjunction with a wavelet transform, a discrete wavelet transform and a contourlet transform to carry out the watermark embedding and extraction processes. In [28], the authors make use of a Discrete Cosine Transform (DCT) based technique to carry out embedding and blind extraction for copyright protection of RGB images. The authors of [29] also employ a DCT based algorithm by modulating the partly sign-altered average of chosen DCT coefficients that are derived from an 8 × 8 image block. ...
... Semi-fragile watermarks provide selective robustness to a specific set of manipulations which are considered as legitimate and allowable [16]. A non-blind watermarking techniques require a host image (usually the cover) for extraction of the watermark, while blind watermarking techniques don't require it [2,3]. ...
As copyright protection is vital and indispensable, watermarking schemes are employed for securing digital data. We propose a novel (to the best of our knowledge) blind and invisible, semi-fragile image watermarking scheme for embedding coloured watermark inside a coloured cover image. The spatial domain embedding is implemented in such a way that modification made in the pixel values of the cover image is not noticeable by human perception. However, the watermark pixel values can be recovered using a unique decoding mechanism, which has been included in the paper. Extraction of the original cover image using the embedded image is also discussed. The obtained MATLAB implementation results are promising when compared to similar state-of-the-art research work.
... Current digital watermark programs for medical images can be classified into visible watermarking [1] and invisible watermarking [2]. Also, they can be divided into spatial domain [3] and transform domain. ...
Digital imaging and communications in medicine are being applied widely to improve health care for people, and their security attracted our attention when they are transmitted through the Internet. The paper proposes a digital watermarking method for medical images based on digital holography and three-level discrete wavelength transform (DWT) singular value decomposition (SVD), where a live code including privacy information is transformed into digital holography by an improved computer-generated hologram method. The holography then is embedded into the singular values of the LL3 subband wavelet of the medical image. Experimental results show that the proposed method provides sufficient security results against various attacks, especially geometrical attacks.
... 3) Watermark insertion is done in the mid-frequency range of the image increases robustness since removal of midfrequencies rather than the high or low frequency components of the watermarked image significantly affects the watermark as noticed by the human eye. The watermark insertion is performed on the color image, which is assumed of size M × N based on the procedure proposed in [27], [28]. As the first step of the insertion process, the image is transformed from the RBG space to YCbCr color space. ...
Smart Healthcare is envisioned as the combination of traditional healthcare augmented by smart bio-sensors, wearable devices and a plethora of on-body sensors that communicate with smart hospitals, smart emergency response systems, and ambulances, through advanced information and communication technologies. The vision of smart healthcare as part of a smart city relies on the framework of the Internet of Things (IoT) as the underlying core technology that enables the design and operation of a city, whereby smart technology, energy grids, transportation, buildings, communication, and information technology, are all interconnected. The present paper address some of the challenges faced in the IoT infrastructure, specifically secure communication and user authentication in the context of automated analysis of biomedical images and communication of the analysis results and related metadata in a smart healthcare framework. A hardware architecture for a Secure Digital Camera (SDC) integrated with the Secure Better Portable Graphics (SBPG) compression algorithm, suitable for applications in the IoT, is proposed in this paper. The focus of this work is on patient data protection and authentication. The proposed SBPG architecture offers two layers of protection: concurrent encryption and watermarking which address all issues related to security, privacy, and digital rights management (DRM). The experimental results demonstrate that the new compression technique BPG outperforms JPEG in terms of compression quality and compressed file size while providing increased image quality. High performance requirements of BPG have been met by employing two techniques: (1) insertion of an encrypted signature in the center portion of the image, and (2) frequency domain watermarking using block-wise DCT of size 8×8 pixels. These approaches optimize the proposed architecture by decreasing computational complexity while maintaining strong protection, with concomitant increase of the speed of the watermarking and compression processes. A Simulink® prototype for the proposed architecture has been built and tested. To the best of the authors’ knowledge, the hardware architecture for BPG compression with built-in image authentication capability for integration with a secure digital camera is the first one ever proposed.
Digital image watermarking is a technique to protect copyright of the image owner in the world of digital communication, and robustness is the major property to be addressed effectively. We propose an invisible hybrid watermarking scheme which is composed of blind and non-blind watermarking techniques. First, blind scheme is used as inner watermarking scheme and then non-blind watermarking scheme as outer watermarking scheme. A secret binary image is taken as a watermark and is embedded in an inner cover image using discrete wavelet transformation (DWT) with the help of the blind watermarking scheme in association with predefined binary digit sequence block and gain factor \({\varvec{\upalpha }}\) to get inner watermarked image. Then, this inner watermarked image is embedded into an outer cover image using DWT and singular value decomposition by non-blind watermarking technique to get hybrid watermarked image. On the contrary, to extract the secret binary image, first non-blind watermark extraction and then blind watermark extraction techniques are used. From the experimental results, it is shown that this hybrid watermarking approach is robust against—rotation, JPEG compression, salt and pepper noise, Gaussian noise, speckle noise and Poisson noise.
The importance of digital images in the field of health care made major impact in the recent years. There is need for protecting the medical images from unauthorized usage and watermarking serves well in this situations. Digital medical Image watermarking is the procedure of protecting the medical image content by inserting the watermark into it. The major objective of the image watermarking technique is to develop an algorithm with high imperceptibility. To achieve this, this paper proposed the image watermarking algorithm in wavelet transformation (IDWT) using the singular value decomposition (SVD) and particle swarm optimization (PSO). The improved DWT is applied to the medical image to retrieve the invariant wavelet domain. The watermark is inserted in to the selected region by modifying the values of the coefficients in the image using threshold function. The scaling factors are optimized using the PSO algorithm. The performance of the proposed model is evaluated using the existing schemes similar to the properties of the proposed model. The normalized coefficient (NC) and Peak Signal to Noise Ratio (PSNR) is considered to evaluate the similarity between the medical image and watermarked medical image. The proposed algorithm showed improved performance in terms of imperceptibility and robustness.
In this paper, a robust additive image watermarking system operating in the Dual Tree Complex Wavelet Transform (DTCWT) domain is proposed. The system takes advantage of a new perceptual masking model that exploits the Human Visual System (HVS) characteristics at the embedding stage. It also uses an efficient watermark detection structure, called the Rao-test, to verify the presence of the candidate watermark. This structure relies on the statistical modeling of high frequency DTCWT coefficients by the Generalized Gaussian distribution. Experimental results show that the proposed system outperforms related state-of-the-art watermarking systems in terms of imperceptibility and robustness.
