Copyright Protection of Color Imaging Using Robust-Encoded Watermarking

In this paper we present a robust-encoded watermarking method applied to color images for copyright protection, which presents robustness against several geometric and signal processing distortions. Trade-off between payload, robustness and imperceptibility is a very important aspect which has to be considered when a watermark algorithm is designed. In our proposed scheme, previously to be embedded into the image, the watermark signal is encoded using a convolutional encoder, which can perform forward error correction achieving better robustness performance. Then, the embedding process is carried out through the discrete cosine transform domain (DCT) of an image using the image normalization technique to accomplish robustness against geometric and signal processing distortions. The embedded watermark coded bits are extracted and decoded using the Viterbi algorithm. In order to determine the presence or absence of the watermark into the image we compute the bit error rate (BER) between the recovered and the original watermark data sequence. The quality of the watermarked image is measured using the well-known indices: Peak Signal to Noise Ratio (PSNR), Visual Information Fidelity (VIF) and Structural Similarity Index (SSIM). The color difference between the watermarked and original images is obtained by using the Normalized Color Difference (NCD) measure. The experimental results show that the proposed method provides good performance in terms of imperceptibility and robustness. The comparison among the proposed and previously reported methods based on different techniques is also provided

Protection of an intrusion detection engine with watermarking in ad hoc networks

Mobile ad hoc networks have received great attention in recent years, mainly due to the evolution of wireless networking and mobile computing hardware. Nevertheless, many inherent vulnerabilities exist in mobile ad hoc networks and their applications that affect the security of wireless transactions. As intrusion prevention mechanisms, such as encryption and authentication, are not sufficient we need a second line of defense, Intrusion Detection. In this pa-per we present an intrusion detection engine based on neural networks and a protection method based on watermarking techniques. In particular, we exploit information visualization and machine learning techniques in order to achieve intrusion detection and we authenticate the maps produced by the application of the intelligent techniques using a novel combined watermarking embedding method. The performance of the proposed model is evaluated under different traffic conditions, mobility patterns and visualization metrics

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

A digital signature and watermarking based authentication system for JPEG2000 images

In this thesis, digital signature based authentication system was introduced, which is able to protect JPEG2000 images in different flavors, including fragile authentication and semi-fragile authentication. The fragile authentication is to protect the image at code-stream level, and the semi-fragile is to protect the image at the content level. The semi-fragile can be further classified into lossy and lossless authentication. With lossless authentication, the original image can be recovered after verification. The lossless authentication and the new image compression standard, JPEG2000 is mainly discussed in this thesis

Towards Optimal Copyright Protection Using Neural Networks Based Digital Image Watermarking

In the field of digital watermarking, digital image watermarking for copyright protection has attracted a lot of attention in the research community. Digital watermarking contains varies techniques for protecting the digital content. Among all those techniques,Discrete Wavelet Transform (DWT) provides higher image imperceptibility and robustness. Over the years, researchers have been designing watermarking techniques with robustness in mind, in order for the watermark to be resistant against any image processing techniques. Furthermore, the requirements of a good watermarking technique includes a tradeoff between robustness, image quality (imperceptibility) and capacity. In this paper, we have done an extensive literature review for the existing DWT techniques and those combined with other techniques such as Neural Networks. In addition to that, we have discuss the contribution of Neural Networks in copyright protection. Finally we reached our goal in which we identified the research gaps existed in the current watermarking schemes. So that, it will be easily to obtain an optimal techniques to make the watermark object robust to attacks while maintaining the imperceptibility to enhance the copyright protection

Multiple Content Adaptive Intelligent Watermarking Schemes for the Protection of Blocks of a Document Image

Most of the documents contain different types of information such as white space, static information and dynamic information or mix of static and dynamic information. In this paper, multiple watermarking schemes are proposed for protection of the information content. The proposed approach comprises of three phases. In Phase-1, the edges of the source document image are extracted and the edge image is decomposed into blocks of uniform size. In Phase-2, GLCM features like energy, homogeneity, contrast and correlation are extracted from each block and the blocks are classified as no-information, static, dynamic and mix of static and dynamic information content blocks. The adjacent blocks of same type are merged together into a single block. Each block is watermarked in Phase-3. The type and amount of watermarking applied is decided intelligently and adaptively based on the classification of the blocks which results in improving embedding capacity and reducing time complexity incurred during watermarking. Experiments are conducted exhaustively on all the images in the corpus. The experimental evaluations exhibit better classification of segments based on information content in the block. The proposed technique also outperforms the existing watermarking schemes on document images in terms of robustness, accuracy of tamper detection and recovery