General Framework of Reversible Watermarking Based on Asymmetric Histogram Shifting of Prediction Error

This paper presents a general framework for the reversible watermarking based on asymmetric histogram shifting of prediction error, which is inspired by reversible watermarking of prediction error. Different from the conventional algorithms using single-prediction scheme to create symmetric histogram, the proposed method employs a multi-prediction scheme, which calculates multiple prediction values for the pixels. Then, the suitable value would be selected by two dual asymmetric selection functions to construct two asymmetric error histograms. Finally, the watermark is embedded in the two error histograms separately utilizing a complementary embedding strategy. The proposed framework provides a new perspective for the research of reversible watermarking, which brings about many benefits for the information security

Digital rights management techniques for H.264 video

This work aims to present a number of low-complexity digital rights management (DRM) methodologies for the H.264 standard. Initially, requirements to enforce DRM are analyzed and understood. Based on these requirements, a framework is constructed which puts forth different possibilities that can be explored to satisfy the objective. To implement computationally efficient DRM methods, watermarking and content based copy detection are then chosen as the preferred methodologies. The first approach is based on robust watermarking which modifies the DC residuals of 4×4 macroblocks within I-frames. Robust watermarks are appropriate for content protection and proving ownership. Experimental results show that the technique exhibits encouraging rate-distortion (R-D) characteristics while at the same time being computationally efficient. The problem of content authentication is addressed with the help of two methodologies: irreversible and reversible watermarks. The first approach utilizes the highest frequency coefficient within 4×4 blocks of the I-frames after CAVLC en- tropy encoding to embed a watermark. The technique was found to be very effect- ive in detecting tampering. The second approach applies the difference expansion (DE) method on IPCM macroblocks within P-frames to embed a high-capacity reversible watermark. Experiments prove the technique to be not only fragile and reversible but also exhibiting minimal variation in its R-D characteristics. The final methodology adopted to enforce DRM for H.264 video is based on the concept of signature generation and matching. Specific types of macroblocks within each predefined region of an I-, B- and P-frame are counted at regular intervals in a video clip and an ordinal matrix is constructed based on their count. The matrix is considered to be the signature of that video clip and is matched with longer video sequences to detect copies within them. Simulation results show that the matching methodology is capable of not only detecting copies but also its location within a longer video sequence. Performance analysis depict acceptable false positive and false negative rates and encouraging receiver operating charac- teristics. Finally, the time taken to match and locate copies is significantly low which makes it ideal for use in broadcast and streaming applications

Reversible Deep Neural Network Watermarking:Matching the Floating-point Weights

Static deep neural network (DNN) watermarking embeds watermarks into the weights of DNN model by irreversible methods, but this will cause permanent damage to watermarked model and can not meet the requirements of integrity authentication. For these reasons, reversible data hiding (RDH) seems more attractive for the copyright protection of DNNs. This paper proposes a novel RDH-based static DNN watermarking method by improving the non-reversible quantization index modulation (QIM). Targeting the floating-point weights of DNNs, the idea of our RDH method is to add a scaled quantization error back to the cover object. Two schemes are designed to realize the integrity protection and legitimate authentication of DNNs. Simulation results on training loss and classification accuracy justify the superior feasibility, effectiveness and adaptability of the proposed method over histogram shifting (HS).Comment: 21 page

Reversible Watermarking Using Prediction-Error Expansion and Extreme Learning Machine

Currently, the research for reversible watermarking focuses on the decreasing of image distortion. Aiming at this issue, this paper presents an improvement method to lower the embedding distortion based on the prediction-error expansion (PE) technique. Firstly, the extreme learning machine (ELM) with good generalization ability is utilized to enhance the prediction accuracy for image pixel value during the watermarking embedding, and the lower prediction error results in the reduction of image distortion. Moreover, an optimization operation for strengthening the performance of ELM is taken to further lessen the embedding distortion. With two popular predictors, that is, median edge detector (MED) predictor and gradient-adjusted predictor (GAP), the experimental results for the classical images and Kodak image set indicate that the proposed scheme achieves improvement for the lowering of image distortion compared with the classical PE scheme proposed by Thodi et al. and outperforms the improvement method presented by Coltuc and other existing approaches

Study and Implementation of Watermarking Algorithms

Water Making is the process of embedding data called a watermark into a multimedia object such that watermark can be detected or extracted later to make an assertion about the object. The object may be an audio, image or video. A copy of a digital image is identical to the original. This has in many instances, led to the use of digital content with malicious intent. One way to protect multimedia data against illegal recording and retransmission is to embed a signal, called digital signature or copyright label or watermark that authenticates the owner of the data. Data hiding, schemes to embed secondary data in digital media, have made considerable progress in recent years and attracted attention from both academia and industry. Techniques have been proposed for a variety of applications, including ownership protection, authentication and access control. Imperceptibility, robustness against moderate processing such as compression, and the ability to hide many bits are the basic but rat..

Adaptive optics for laser processing

The overall aim of the work presented in this thesis is to develop an adaptive optics (AO) technique for application to laser-based manufacturing processes. The Gaussian beam shape typically coming from a laser is not always ideal for laser machining. Wavefront modulators, such as deformable mirrors (DM) and liquid crystal spatial light modulators (SLM), enable the generation of a variety of beam shapes and furthermore offer the ability to alter the beam shape during the actual process. The benefits of modifying the Gaussian beam shape by means of a deformable mirror towards a square flat top profile for nanosecond laser marking and towards a ring shape intensity distribution for millisecond laser drilling are presented. Limitations of the beam shaping capabilities of DM are discussed. The application of a spatial light modulator to nanosecond laser micromachining is demonstrated for the first time. Heat sinking is introduced to increase the power handling capabilities. Controllable complex beam shapes can be generated with sufficient intensity for direct laser marking. Conventional SLM devices suffer from flickering and hence a process synchronisation is introduced to compensate for its impact on the laser machining result. For alternative SLM devices this novel technique can be beneficial when fast changes of the beam shape during the laser machining are required. The dynamic nature of SLMs is utilised to improve the marking quality by reducing the inherent speckle distribution of the generated beam shape. In addition, adaptive feedback on the intensity distribution can further improve the quality of the laser machining. In general, beam shaping by means of AO devices enables an increased flexibility and an improved process control, and thus has a significant potential to be used in laser materials processing

Measurements, Models, Systems and Design

531 s.

Preserving data integrity of encoded medical images: the LAR compression framework

International audienceThrough the development of medical imaging systems and their integration into a complete information system, the need for advanced joint coding and network services becomes predominant. PACS (Picture Archiving and Communication System) aims to acquire, store and compress, retrieve, present and distribute medical images. These systems have to be accessible via the Internet or wireless channels. Thus protection processes against transmission errors have to be added to get a powerful joint source-channel coding tool. Moreover, these sensitive data require confidentiality and privacy for both archiving and transmission purposes, leading to use cryptography and data embedding solutions. This chapter introduces data integrity protection and developed dedicated tools of content protection and secure bitstream transmission for medical encoded image purposes. In particular, the LAR image coding method is defined together with advanced securization services

Intraocular Lens

The first clinical application of intraocular lens (IOL) goes back to 1949 when Dr. Harold Ridley successfully implanted a PMMA IOL into an eye on 29 November 1949. This innovation is a big step forward for cataract surgery. With development of the IOL material and biocompatibility, more and more IOL types have been used in clinical ophthalmology. This book is the fruit of worldwide cooperation between clinical teams. In this book we discuss the IOL materials and design, aberration and astigmatism correction with IOL, entopic phenomenon of IOL, myopia and phakic IOL, and secondary IOL techniques. We believe that this content provides the readers with a comprehensive knowledge of the latest developments of IOL