Fragile watermarking for image authentication using dyadic walsh ordering

A digital image is subjected to the most manipulation. This is driven by the easy manipulating process through image editing software which is growing rapidly. These problems can be solved through the watermarking model as an active authentication system for the image. One of the most popular methods is Singular Value Decomposition (SVD) which has good imperceptibility and detection capabilities. Nevertheless, SVD has high complexity and can only utilize one singular matrix S, and ignore two orthogonal matrices. This paper proposes the use of the Walsh matrix with dyadic ordering to generate a new S matrix without the orthogonal matrices. The experimental results showed that the proposed method was able to reduce computational time by 22% and 13% compared to the SVD-based method and similar methods based on the Hadamard matrix respectively. This research can be used as a reference to speed up the computing time of the watermarking methods without compromising the level of imperceptibility and authentication

Secure and Robust Fragile Watermarking Scheme for Medical Images

Over the past decade advances in computer-based communication and health services, the need for image security becomes urgent to address the requirements of both safety and non-safety in medical applications. This paper proposes a new fragile watermarking based scheme for image authentication and self-recovery for medical applications. The proposed scheme locates image tampering as well as recovers the original image. A host image is broken into 4×4 blocks and Singular Value Decomposition (SVD) is applied by inserting the traces of block wise SVD into the Least Significant Bit (LSB) of the image pixels to figure out the transformation in the original image. Two authentication bits namely block authentication and self-recovery bits were used to survive the vector quantization attack. The insertion of self-recovery bits is determined with Arnold transformation, which recovers the original image even after a high tampering rate. SVD-based watermarking information improves the image authentication and provides a way to detect different attacked area. The proposed scheme is tested against different types of attacks such are text removal attack, text insertion attack, and copy and paste attack

QAM-DWT-SVD Based Watermarking Scheme for Medical Images

This paper presents a new semi-blind image watermarking system for medical applications. The new scheme utilizes Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT) to embed a textual data into original medical images. In particular, text characters are encoded by a Quadrature Amplitude Modulation (QAM-16). In order to increase the security of the system and protect then the watermark from several attacks, the embedded data is submitted to Arnold Transform before inserting it into the host medical image. To evaluate the performances of the scheme, several medical images have been used in the experiments. Simulation results show that the proposed watermarking system ensures good imperceptibility and high robustness against several attacks

Wavelet based digital art protection

This thesis objective is to provide a robust watermarking algorithm to protect digital images. The proposed algorithm is using wavelet-based watermarking in which we are investigating how embedding in high-frequency subbands and low-frequency subbands would affect the robustness of the watermark while facing typical signal processing attacks

AN INVESTIGATION OF DIFFERENT VIDEO WATERMARKING TECHNIQUES

Watermarking is an advanced technology that identifies to solve the problem of illegal manipulation and distribution of digital data. It is the art of hiding the copyright information into host such that the embedded data is imperceptible. The covers in the forms of digital multimedia object, namely image, audio and video. The extensive literature collected related to the performance improvement of video watermarking techniques is critically reviewed and presented in this paper. Also, comprehensive review of the literature on the evolution of various video watermarking techniques to achieve robustness and to maintain the quality of watermarked video sequences

Are Social Networks Watermarking Us or Are We (Unawarely) Watermarking Ourself?

In the last decade, Social Networks (SNs) have deeply changed many aspects of society, and one of the most widespread behaviours is the sharing of pictures. However, malicious users often exploit shared pictures to create fake profiles leading to the growth of cybercrime. Thus, keeping in mind this scenario, authorship attribution and verification through image watermarking techniques are becoming more and more important. In this paper, firstly, we investigate how 13 most popular SNs treat the uploaded pictures, in order to identify a possible implementation of image watermarking techniques by respective SNs. Secondly, on these 13 SNs, we test the robustness of several image watermarking algorithms. Finally, we verify whether a method based on the Photo-Response Non-Uniformity (PRNU) technique can be successfully used as a watermarking approach for authorship attribution and verification of pictures on SNs. The proposed method is robust enough in spite of the fact that the pictures get downgraded during the uploading process by SNs. The results of our analysis on a real dataset of 8,400 pictures show that the proposed method is more effective than other watermarking techniques and can help to address serious questions about privacy and security on SNs.Comment: 43 pages, 6 figure

AuSR2: Image watermarking technique for authentication and self-recovery with image texture preservation

This paper presents an image watermarking technique for authentication and self-recovery called AuSR2. The AuSR2 scheme partitions the cover image into 3 × 3 non-overlapping blocks. The watermark data is embedded into two Least Significant Bit (LSB), consisting of two authentication bits and 16 recovery bits for each block. The texture of each block is preserved in the recovery data. Thus, each tampered pixel can be recovered independently instead of using the average block. The recovery process may introduce the tamper coincidence problem, which can be solved using image inpainting. The AuSR2 implements the LSB shifting algorithm to increase the imperceptibility by 2.8%. The experimental results confirm that the AuSR2 can accurately detect the tampering area up to 100%. The AuSR2 can recover the tampered image with a PSNR value of 38.11 dB under a 10% tampering rate. The comparative analysis proves the superiority of the AuSR2 compared to the existing scheme

A Study in Image Watermarking Schemes using Neural Networks

The digital watermarking technique, an effective way to protect image, has become the research focus on neural network. The purpose of this paper is to provide a brief study on broad theories and discuss the different types of neural networks for image watermarking. Most of the research interest image watermarking based on neural network in discrete wavelet transform or discrete cosine transform. Generally image watermarking based on neural network to solve the problem on to reduce the error, improve the rate of the learning, achieves goods imperceptibility and robustness. It will be useful for researches to implement effective image watermarking by using neural network

A robust region-adaptive digital image watermarking system

Digital image watermarking techniques have drawn the attention of researchers and practitioners as a means of protecting copyright in digital images. The technique involves a subset of information-hiding technologies, which work by embedding information into a host image without perceptually altering the appearance of the host image. Despite progress in digital image watermarking technology, the main objectives of the majority of research in this area remain improvements in the imperceptibility and robustness of the watermark to attacks. Watermark attacks are often deliberately applied to a watermarked image in order to remove or destroy any watermark signals in the host data. The purpose of the attack is. aimed at disabling the copyright protection system offered by watermarking technology. Our research in the area of watermark attacks found a number of different types, which can be classified into a number of categories including removal attacks, geometry attacks, cryptographic attacks and protocol attacks. Our research also found that both pixel domain and transform domain watermarking techniques share similar levels of sensitivity to these attacks. The experiment conducted to analyse the effects of different attacks on watermarked data provided us with the conclusion that each attack affects the high and low frequency part of the watermarked image spectrum differently. Furthermore, the findings also showed that the effects of an attack can be alleviated by using a watermark image with a similar frequency spectrum to that of the host image. The results of this experiment led us to a hypothesis that would be proven by applying a watermark embedding technique which takes into account all of the above phenomena. We call this technique 'region-adaptive watermarking'. Region-adaptive watermarking is a novel embedding technique where the watermark data is embedded in different regions of the host image. The embedding algorithms use discrete wavelet transforms and a combination of discrete wavelet transforms and singular value decomposition, respectively. This technique is derived from the earlier hypothesis that the robustness of a watermarking process can be improved by using watermark data in the frequency spectrum that are not too dissimilar to that of the host data. To facilitate this, the technique utilises dual watermarking technologies and embeds parts of the watermark images into selected regions of the host image. Our experiment shows that our technique improves the robustness of the watermark data to image processing and geometric attacks, thus validating the earlier hypothesis. In addition to improving the robustness of the watermark to attacks, we can also show a novel use for the region-adaptive watermarking technique as a means of detecting whether certain types of attack have occurred. This is a unique feature of our watermarking algorithm, which separates it from other state-of-the-art techniques. The watermark detection process uses coefficients derived from the region-adaptive watermarking algorithm in a linear classifier. The experiment conducted to validate this feature shows that, on average, 94.5% of all watermark attacks can be correctly detected and identified