New watermarking methods for digital images.

The phenomenal spread of the Internet places an enormous demand on content-ownership-validation. In this thesis, four new image-watermarking methods are presented. One method is based on discrete-wavelet-transformation (DWT) only while the rest are based on DWT and singular-value-decomposition (SVD) ensemble. The main target for this thesis is to reach a new blind-watermarking-method. Method IV presents such watermark using QR-codes. The use of QR-codes in watermarking is novel. The choice of such application is based on the fact that QR-Codes have errors self-correction-capability of 5% or higher which satisfies the nature of digital-image-processing. Results show that the proposed-methods introduced minimal distortion to the watermarked images as compared to other methods and are robust against JPEG, resizing and other attacks. Moreover, watermarking-method-II provides a solution to the detection of false watermark in the literature. Finally, method IV presents a new QR-code guided watermarking-approach that can be used as a steganography as well. --Leaf ii.The original print copy of this thesis may be available here: http://wizard.unbc.ca/record=b183575

Digital video watermarking techniques for secure multimedia creation and delivery.

Chan Pik-Wah.Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.Includes bibliographical references (leaves 111-130).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.ivChapter 1 --- Introduction --- p.1Chapter 1.1 --- Background --- p.1Chapter 1.2 --- Research Objective --- p.3Chapter 1.3 --- Contributions --- p.4Chapter 1.4 --- The Structure of this Thesis --- p.6Chapter 2 --- Literature Review --- p.7Chapter 2.1 --- Security in Multimedia Communications --- p.8Chapter 2.2 --- Cryptography --- p.11Chapter 2.3 --- Digital Watermarking --- p.14Chapter 2.4 --- Essential Ingredients for Video Watermarking --- p.16Chapter 2.4.1 --- Fidelity --- p.16Chapter 2.4.2 --- Robustness --- p.17Chapter 2.4.3 --- Use of Keys --- p.19Chapter 2.4.4 --- Blind Detection --- p.20Chapter 2.4.5 --- Capacity and Speed --- p.20Chapter 2.4.6 --- Statistical Imperceptibility --- p.21Chapter 2.4.7 --- Low Error Probability --- p.21Chapter 2.4.8 --- Real-time Detector Complexity --- p.21Chapter 2.5 --- Review on Video Watermarking Techniques --- p.22Chapter 2.5.1 --- Video Watermarking --- p.25Chapter 2.5.2 --- Spatial Domain Watermarks --- p.26Chapter 2.5.3 --- Frequency Domain Watermarks --- p.30Chapter 2.5.4 --- Watermarks Based on MPEG Coding Struc- tures --- p.35Chapter 2.6 --- Comparison between Different Watermarking Schemes --- p.38Chapter 3 --- Novel Watermarking Schemes --- p.42Chapter 3.1 --- A Scene-based Video Watermarking Scheme --- p.42Chapter 3.1.1 --- Watermark Preprocess --- p.44Chapter 3.1.2 --- Video Preprocess --- p.46Chapter 3.1.3 --- Watermark Embedding --- p.48Chapter 3.1.4 --- Watermark Detection --- p.50Chapter 3.2 --- Theoretical Analysis --- p.52Chapter 3.2.1 --- Performance --- p.52Chapter 3.2.2 --- Capacity --- p.56Chapter 3.3 --- A Hybrid Watermarking Scheme --- p.60Chapter 3.3.1 --- Visual-audio Hybrid Watermarking --- p.61Chapter 3.3.2 --- Hybrid Approach with Different Water- marking Schemes --- p.69Chapter 3.4 --- A Genetic Algorithm-based Video Watermarking Scheme --- p.73Chapter 3.4.1 --- Watermarking Scheme --- p.75Chapter 3.4.2 --- Problem Modelling --- p.76Chapter 3.4.3 --- Chromosome Encoding --- p.79Chapter 3.4.4 --- Genetic Operators --- p.80Chapter 4 --- Experimental Results --- p.85Chapter 4.1 --- Test on Robustness --- p.85Chapter 4.1.1 --- Experiment with Frame Dropping --- p.87Chapter 4.1.2 --- Experiment with Frame Averaging and Sta- tistical Analysis --- p.89Chapter 4.1.3 --- Experiment with Lossy Compression --- p.90Chapter 4.1.4 --- Test of Robustness with StirMark 4.0 --- p.92Chapter 4.1.5 --- Overall Comparison --- p.98Chapter 4.2 --- Test on Fidelity --- p.100Chapter 4.2.1 --- Parameter(s) Setting --- p.101Chapter 4.2.2 --- Evaluate with PSNR --- p.101Chapter 4.2.3 --- Evaluate with MAD --- p.102Chapter 4.3 --- Other Features of the Scheme --- p.105Chapter 4.4 --- Conclusion --- p.106Chapter 5 --- Conclusion --- p.108Bibliography --- p.11

Segmentation, registration,and selective watermarking of retinal images

In this dissertation, I investigated some fundamental issues related to medical image segmentation, registration, and watermarking. I used color retinal fundus images to perform my study because of the rich representation of different objects (blood vessels, microaneurysms, hemorrhages, exudates, etc.) that are pathologically important and have close resemblance in shapes and colors. To attack this complex subject, I developed a divide-and-conquer strategy to address related issues step-by-step and to optimize the parameters of different algorithm steps. Most, if not all, objects in our discussion are related. The algorithms for detection, registration, and protection of different objects need to consider how to differentiate the foreground from the background and be able to correctly characterize the features of the image objects and their geometric properties. To address these problems, I characterized the shapes of blood vessels in retinal images and proposed the algorithms to extract the features of blood vessels. A tracing algorithm was developed for the detection of blood vessels along the vascular network. Due to the noise interference and various image qualities, the robust segmentation techniques were used for the accurate characterization of the objects shapes and verification. Based on the segmentation results, a registration algorithm was developed, which uses the bifurcation and cross-over points of blood vessels to establish the correspondence between the images and derive the transformation that aligns the images. A Region-of-Interest (ROI) based watermarking scheme was proposed for image authenticity. It uses linear segments extracted from the image as reference locations for embedding and detecting watermark. Global and locally-randomized synchronization schemes were proposed for bit-sequence synchronization of a watermark. The scheme is robust against common image processing and geometric distortions (rotation and scaling), and it can detect alternations such as moving or removing of the image content

Digital Watermarking of Images towards Content Protection.

With the rapid growth of the internet and digital media techniques over the last decade, multimedia data such as images, video and audio can easily be copied, altered and distributed over the internet without any loss in quality. Therefore, protection of ownership of multimedia data has become a very significant and challenging issue. Three novel image watermarking algorithms have been designed and implemented for copyright protection. The first proposed algorithm is based on embedding multiple watermarks in the blue channel of colour images to achieve more robustness against attacks. The second proposed algorithm aims to achieve better trade-offs between imperceptibility and robustness requirements of a digital watermarking system. It embeds a watermark in adaptive manner via classification of DCT blocks with three levels: smooth, edges and texture, implemented in the DCT domain by analyzing the values of AC coefficients. The third algorithm aims to achieve robustness against geometric attacks, which can desynchronize the location of the watermark and hence cause incorrect watermark detection. It uses geometrically invariant feature points and image normalization to overcome the problem of synchronization errors caused by geometric attacks. Experimental results show that the proposed algorithms are robust and outperform related techniques found in literature

MediaSync: Handbook on Multimedia Synchronization

This book provides an approachable overview of the most recent advances in the fascinating field of media synchronization (mediasync), gathering contributions from the most representative and influential experts. Understanding the challenges of this field in the current multi-sensory, multi-device, and multi-protocol world is not an easy task. The book revisits the foundations of mediasync, including theoretical frameworks and models, highlights ongoing research efforts, like hybrid broadband broadcast (HBB) delivery and users' perception modeling (i.e., Quality of Experience or QoE), and paves the way for the future (e.g., towards the deployment of multi-sensory and ultra-realistic experiences). Although many advances around mediasync have been devised and deployed, this area of research is getting renewed attention to overcome remaining challenges in the next-generation (heterogeneous and ubiquitous) media ecosystem. Given the significant advances in this research area, its current relevance and the multiple disciplines it involves, the availability of a reference book on mediasync becomes necessary. This book fills the gap in this context. In particular, it addresses key aspects and reviews the most relevant contributions within the mediasync research space, from different perspectives. Mediasync: Handbook on Multimedia Synchronization is the perfect companion for scholars and practitioners that want to acquire strong knowledge about this research area, and also approach the challenges behind ensuring the best mediated experiences, by providing the adequate synchronization between the media elements that constitute these experiences

Music Encoding Conference Proceedings 2021, 19–22 July, 2021 University of Alicante (Spain): Onsite & Online

Este documento incluye los artículos y pósters presentados en el Music Encoding Conference 2021 realizado en Alicante entre el 19 y el 22 de julio de 2022.Funded by project Multiscore, MCIN/AEI/10.13039/50110001103

Enhanced coding, clock recovery and detection for a magnetic credit card

Merged with duplicate record 10026.1/2299 on 03.04.2017 by CS (TIS)This thesis describes the background, investigation and construction of a system for storing data on the magnetic stripe of a standard three-inch plastic credit in: inch card. Investigation shows that the information storage limit within a 3.375 in by 0.11 in rectangle of the stripe is bounded to about 20 kBytes. Practical issues limit the data storage to around 300 Bytes with a low raw error rate: a four-fold density increase over the standard. Removal of the timing jitter (that is prob-' ably caused by the magnetic medium particle size) would increase the limit to 1500 Bytes with no other system changes. This is enough capacity for either a small digital passport photograph or a digitized signature: making it possible to remove printed versions from the surface of the card. To achieve even these modest gains has required the development of a new variable rate code that is more resilient to timing errors than other codes in its efficiency class. The tabulation of the effects of timing errors required the construction of a new code metric and self-recovering decoders. In addition, a new method of timing recovery, based on the signal 'snatches' has been invented to increase the rapidity with which a Bayesian decoder can track the changing velocity of a hand-swiped card. The timing recovery and Bayesian detector have been integrated into one computation (software) unit that is self-contained and can decode a general class of (d, k) constrained codes. Additionally, the unit has a signal truncation mechanism to alleviate some of the effects of non-linear distortion that are present when a magnetic card is read with a magneto-resistive magnetic sensor that has been driven beyond its bias magnetization. While the storage density is low and the total storage capacity is meagre in comparison with contemporary storage devices, the high density card may still have a niche role to play in society. Nevertheless, in the face of the Smart card its long term outlook is uncertain. However, several areas of coding and detection under short-duration extreme conditions have brought new decoding methods to light. The scope of these methods is not limited just to the credit card

Digital Image Processing

Newspapers and the popular scientific press today publish many examples of highly impressive images. These images range, for example, from those showing regions of star birth in the distant Universe to the extent of the stratospheric ozone depletion over Antarctica in springtime, and to those regions of the human brain affected by Alzheimer’s disease. Processed digitally to generate spectacular images, often in false colour, they all make an immediate and deep impact on the viewer’s imagination and understanding. Professor Jonathan Blackledge’s erudite but very useful new treatise Digital Image Processing: Mathematical and Computational Methods explains both the underlying theory and the techniques used to produce such images in considerable detail. It also provides many valuable example problems - and their solutions - so that the reader can test his/her grasp of the physical, mathematical and numerical aspects of the particular topics and methods discussed. As such, this magnum opus complements the author’s earlier work Digital Signal Processing. Both books are a wonderful resource for students who wish to make their careers in this fascinating and rapidly developing field which has an ever increasing number of areas of application. The strengths of this large book lie in: • excellent explanatory introduction to the subject; • thorough treatment of the theoretical foundations, dealing with both electromagnetic and acoustic wave scattering and allied techniques; • comprehensive discussion of all the basic principles, the mathematical transforms (e.g. the Fourier and Radon transforms), their interrelationships and, in particular, Born scattering theory and its application to imaging systems modelling; discussion in detail - including the assumptions and limitations - of optical imaging, seismic imaging, medical imaging (using ultrasound), X-ray computer aided tomography, tomography when the wavelength of the probing radiation is of the same order as the dimensions of the scatterer, Synthetic Aperture Radar (airborne or spaceborne), digital watermarking and holography; detail devoted to the methods of implementation of the analytical schemes in various case studies and also as numerical packages (especially in C/C++); • coverage of deconvolution, de-blurring (or sharpening) an image, maximum entropy techniques, Bayesian estimators, techniques for enhancing the dynamic range of an image, methods of filtering images and techniques for noise reduction; • discussion of thresholding, techniques for detecting edges in an image and for contrast stretching, stochastic scattering (random walk models) and models for characterizing an image statistically; • investigation of fractal images, fractal dimension segmentation, image texture, the coding and storing of large quantities of data, and image compression such as JPEG; • valuable summary of the important results obtained in each Chapter given at its end; • suggestions for further reading at the end of each Chapter. I warmly commend this text to all readers, and trust that they will find it to be invaluable. Professor Michael J Rycroft Visiting Professor at the International Space University, Strasbourg, France, and at Cranfield University, England