Watermark Embedding Procedure Research Articles

Digital Image Watermarking Technique Based on Different Attacks

Digital watermarking is used to hide the information inside a signal, which cannot be easily extracted by the third party. Its widely used application is copyright protection of digital information. It is different from the encryption in the sense that it allows the user to access, view and interpret the signal but protect the ownership of the content. One of the current research areas is to protect digital watermark inside the information so that ownership of the information cannot be claimed by third party. With a lot of information available on various search engines, to protect the ownership of information is a crucial area of research. In recent year, several digital watermarking techniques are presented based on discrete cosine transform (DCT), discrete wavelets transform (DWT) and discrete fourier transforms (DFT). In this paper, we proposed an algorithm for digital image watermarking technique based on singular value decomposition; both of the L and U components are explored for watermarking algorithm. This technique refers to the watermark embedding procedure and watermark extracting procedure. Digital image watermarking techniques for copyright protection is robust. The experimental results prove that the quality of the watermarked image is good and that there is strong resistant against many attacks. The image watermarking techniques help to achieve artificial intelligence. Digital image watermarking is the most effective solution in this area and its use to protect the information is increasingly exponentially day by day.

A Video Watermark Method Based on Chaotic Encryption

An effective and integrated video watermark scheme mainly includes watermark generation, watermark embedding, watermark detecting, and watermark attack. The watermark data come from a meaningful binary image encrypted by two-dimensional chaotic stream encryption to improve watermark security. In the procedure of watermark embedding, watermarks are embedded into the random selected video frames through modifying the DCT coefficients. After robust and frame processes, watermarks can be mainly extracted and identified through watermark extracting algorithm. The experimental results show that the proposed video watermark method has some performances of security, imperceptibility and robustness.

Robust and Geometric Invariant Watermarking Scheme using Block and Gray-Level Histograms

As one of the crucial problems in watermarking, robustness against geometric distortion and JPEG compression becomes more than challenging and problematic. In this paper, a robust and geometric invariant watermarking scheme using block histogram and intensity-level histograms is proposed. During watermark embedding procedure, we first compute the number of valid intensity-levels of the given image, and group the pixels into blocks of variable size such that each of which has the same number of intensity-levels. Thus the block histogram is generated for the given image. Then the intensity-level histogram of each block is modified according to the embedding bits of the watermark. During the extraction procedure, the block histogram and intensity-level histogram of each block in the watermarked image are generated in a similar manner and the watermark is decoded according to the distribution of the intensity-level histogram in each block. Experimental results show that the proposed scheme is highly robust against not only JPEG compression, but also geometric attacks and common signal processing such as median filtering. The comparison results also show that the proposed scheme outperforms the existing methods in terms of robustness.

Copyright authentication for images with a full counter-propagation neural network

Watermarking is a technique used for digital copyright protection. It has been developed to protect digital media from being illegally reproduced and modified. In this paper, a full counter-propagation neural network (FCNN) is applied to copyright authentication, where the ownership information (watermark) is embedded and detected by a specific FCNN. As opposed to traditional methods, the watermark is stored in the synapses of the FCNN. Because an FCNN has storage and fault tolerance, most attacks do not degrade the quality of the detected watermark image. Moreover, the watermark embedding procedure and detection procedure are integrated into the proposed FCNN. It accomplishes watermark embedding and detection of one or many watermarks using a multi-cover image. The experimental results show that the proposed method is more robust than Deng’s, Hsieh’s, Hsu’s, and Zhang’s methods under different attacks, and that it is imperceptible and authentic.

Adaptive Spread-Transform Dither Modulation Using a New Perceptual Model for Color Image Watermarking

Major challenges of the conventional spread-transform dither modulation (STDM) watermarking approach are two-fold: (i) it exploits a fixed watermarking strength (more particularly, the quantization index step size) to the whole cover image; and (ii) it is fairly vulnerable to the amplitude changes. To tackle the above challenges, an adaptive spread-transform dither modulation (ASTDM) approach is proposed in this paper for conducting robust color image watermarking by incorporating a new perceptual model into the conventional STDM framework. The proposed approach exploits a new perceptual model to adjust the quantization index step sizes according to the local perceptual characteristics of a cover image. Furthermore, in contrast to the conventional Watson's model is vulnerable to the amplitude changes, our proposed new perceptual model makes the luminance masking thresholds be consistent with any amplitude change, while keeping the consistence to the properties of the human visual system. In addition, certain color artifacts could be incurred during the watermark embedding procedure, since some intensity values are perceptibly changed to label the watermark. For that, a color artifact suppression algorithm is proposed by mathematically deriving an upper bound for the intensity values according to the inherent relationship between the saturation and the intensity components. Extensive experiments are conducted using 500 images selected from Corel database to demonstrate the superior performance of the proposed ASTDM approach.

Invertible chaotic fragile watermarking for robust image authentication

Fragile watermarking is a popular method for image authentication. In such schemes, a fragile signal that is sensitive to manipulations is embedded in the image, so that it becomes undetectable after any modification of the original work. Most algorithms focus either on the ability to retrieve the original work after watermark detection (invertibility) or on detecting which image parts have been altered (localization). Furthermore, the majority of fragile watermarking schemes suffer from robustness flaws. We propose a new technique that combines localization and invertibility. Moreover, watermark dependency on the original image and the non-linear watermark embedding procedure guarantees that no malicious attacks will manage to create information leaks.

A Nonoblivious Image Watermarking System Based on Singular Value Decomposition and Texture Segmentation

In this paper, a robust digital image watermarking scheme for copyright protection applications using the singular value decomposition (SVD) is proposed. In this scheme, an entropy masking model has been applied on the host image for the texture segmentation. Moreover, the local luminance and textures of the host image are considered for watermark embedding procedure to increase the robustness of the watermarking scheme. In contrast to all existing SVD-based watermarking systems that have been designed to embed visual watermarks, our system uses a pseudo-random sequence as a watermark. We have tested the performance of our method using a wide variety of image processing attacks on different test images. A comparison is made between the results of our proposed algorithm with those of a wavelet-based method to demonstrate the superior performance of our algorithm. Keywords—Watermarking, copyright protection, singular value decomposition, entropy masking, texture segmentation.

Information hiding at oblivious watermarking scheme upon alternative thresold in spatial domains

In this paper, an intellectual property protection mechanism is proposed by means of an oblivious watermarking scheme. The embedding technique adopted in this paper is based on the modular operation. The modulus is a threshold value which determines how the binary pattern of the watermark is to be embedded into an image. In order to create a better fidelity of the image with the embedded watermark against perception by the human vision system, the random bit-string transformed for the watermark is done first. Then there are two classifications required to create the random bit pattern during the embedding procedure. Afterwards, several frequent tests of image processing are done, such as JPEG compression, diverse filtering treatments, resampling and requantization, etc., to prove and show off the remarkable result that was achieved. Compared to the literature of LSB-like watermark embedding procedure in [9] and as observed from the experiments, not only the advantages emphasized in original research work remain, but in addition it should be pointed out that it is not necessary to check the original image again to extract the embedded watermark. Therefore, it can be fairly stated that the scheme explored in this paper is more efficient than the previous one, and that it is a feasible to cope with the protection of intellectual property for digital image recognition.

Reversible Visible Watermarking and Lossless Recovery of Original Images

In this paper, we propose a reversible visible watermarking algorithm to satisfy a new application scenario where the visible watermark serves as a tag or ownership identifier, but can be completely removed to resume the original image data. It includes two procedures: data hiding and visible watermark embedding. In order to losslessly recover both the watermark-covered and nonwatermark-covered image contents at the receiver end, the payload consists of two reconstruction data packets, one for recovering the watermark-covered region, and the other for the nonwatermark-covered region. The data hiding technique reversibly hides the payload in the image region not covered by the visible watermark. To satisfy the requirements of large capacity and high image quality, our hiding technique is based on data compression and uses a payload-adaptive scheme. It further adopts error diffusion for improving subjective image quality and arithmetic compression using a character-based model for increasing computational efficiency. The visible watermark is securely embedded based on a user-key-controlled embedding mechanism. The data hiding and the visible watermark embedding procedures are integrated into a secure watermarking system by a specially designed user key

A novel fractal image watermarking

A novel watermarking method is proposed to hide a binary watermark into image files compressed by fractal block coding. This watermarking method utilizes a special type of orthogonalization fractal coding method where the fractal affine transform is determined by the range block mean and contrast scaling. Such orthogonalization fractal decoding is a mean-invariant iteration. In contrast, the fractal parameters of classical fractal compression are very sensitive to any change of domain block pool and to common signal and geometric distortion. Hence, it is impossible to directly place a watermark in fractal parameters. The proposed watermark embedding procedure inserts a permutated pseudo-random binary sequence into the quantized range block means. The watermark is detected by computing the correlation coefficient between the original and the extracted watermark. Experimental results show that the proposed fractal watermarking scheme is robust against common signal and geometric distortion such as JPEG compression, low-pass filtering, rescaling, and clipping.