DCT Implementation on GPU

There has been a great progress in the field of graphics processors. Since, there is no rise in the speed of the normal CPU processors; Designers are coming up with multi-core, parallel processors. Because of their popularity in parallel processing, GPUs are becoming more and more attractive for many applications. With the increasing demand in utilizing GPUs, there is a great need to develop operating systems that handle the GPU to full capacity. GPUs offer a very efficient environment for many image processing applications. This thesis explores the processing power of GPUs for digital image compression using Discrete cosine transform

Secure digital documents using Steganography and QR Code

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonWith the increasing use of the Internet several problems have arisen regarding the processing of electronic documents. These include content filtering, content retrieval/search. Moreover, document security has taken a centre stage including copyright protection, broadcast monitoring etc. There is an acute need of an effective tool which can find the identity, location and the time when the document was created so that it can be determined whether or not the contents of the document were tampered with after creation. Owing the sensitivity of the large amounts of data which is processed on a daily basis, verifying the authenticity and integrity of a document is more important now than it ever was. Unsurprisingly document authenticity verification has become the centre of attention in the world of research. Consequently, this research is concerned with creating a tool which deals with the above problem. This research proposes the use of a Quick Response Code as a message carrier for Text Key-print. The Text Key-print is a novel method which employs the basic element of the language (i.e. Characters of the alphabet) in order to achieve authenticity of electronic documents through the transformation of its physical structure into a logical structured relationship. The resultant dimensional matrix is then converted into a binary stream and encapsulated with a serial number or URL inside a Quick response Code (QR code) to form a digital fingerprint mark. For hiding a QR code, two image steganography techniques were developed based upon the spatial and the transform domains. In the spatial domain, three methods were proposed and implemented based on the least significant bit insertion technique and the use of pseudorandom number generator to scatter the message into a set of arbitrary pixels. These methods utilise the three colour channels in the images based on the RGB model based in order to embed one, two or three bits per the eight bit channel which results in three different hiding capacities. The second technique is an adaptive approach in transforming domain where a threshold value is calculated under a predefined location for embedding in order to identify the embedding strength of the embedding technique. The quality of the generated stego images was evaluated using both objective (PSNR) and Subjective (DSCQS) methods to ensure the reliability of our proposed methods. The experimental results revealed that PSNR is not a strong indicator of the perceived stego image quality, but not a bad interpreter also of the actual quality of stego images. Since the visual difference between the cover and the stego image must be absolutely imperceptible to the human visual system, it was logically convenient to ask human observers with different qualifications and experience in the field of image processing to evaluate the perceived quality of the cover and the stego image. Thus, the subjective responses were analysed using statistical measurements to describe the distribution of the scores given by the assessors. Thus, the proposed scheme presents an alternative approach to protect digital documents rather than the traditional techniques of digital signature and watermarking

Privacy-preserving energy management techniques and delay-sensitive transmission strategies for smart grids

The smart grid (SG) is the enhancement of the traditional electricity grid that allows bidirectional flow of electricity and information through the integration of advanced monitoring, communication and control technologies. In this thesis, we focus on important design problems affecting particularly two critical enabling components of the SG infrastructure : smart meters (SMs) and wireless sensor networks (WSNs). SMs measure the energy consumption of the users and transmit their readings to the utility provider in almost real-time. SM readings enable real-time optimization of load management. However, possible misuse of SM readings raises serious privacy concerns for the users. The challenge is thus to design techniques that can increase the privacy of the users while maintaining the monitoring capabilities SMs provide. Demand-side energy management (EM), achieved thanks to the utilization of storage units and alternative energy sources, has emerged as a potential technique to tackle this challenge. WSNs consist of a large number of low power sensors, which monitor physical parameters and transmit their measurements to control centers (CCs) over wireless links. CCs utilize these measurements to reconstruct the system state. For the reliable management of the SG, near real-time and accurate reconstruction of the system state at the CC is crucial. Thus, low complexity delay-constrained transmission strategies, which enable sensors to accurately transmit their measurements to CCs, should be investigated rigorously. To address these challenges, this dissertation investigates and designs privacy-preserving EM techniques for SMs and delay-constrained transmission strategies for WSNs. The proposed EM techniques provide privacy to SM users while maintaining the operational benefits SMs provide. On the other hand, the proposed transmission strategies enable WSNs to meet low latency transmission requirements, which in turn, facilitate real-time and accurate state reconstruction; and hence, the efficient and robust management of the SG. First, we consider an SM system with energy harvesting and storage units. Representing the system with a discrete-time finite state model, we study stochastic EM policies from a privacy-energy efficiency trade-off perspective, where privacy is measured by information leakage rate and energy efficiency is measured by wasted energy rate. We propose EM policies that take stochastic output load decisions based on the harvested energy, the input load and the state of the battery. For the proposed policies, we characterize the fundamental trade-off between user's privacy and energy efficiency. Second, we consider an SM system with a storage unit. Considering a discrete-time power consumption and pricing model, we study EM policies from a privacy-cost trade-off perspective, where privacy is measured by the load variance as well as mutual information. Assuming non-causal knowledge of the power demand profile and prices, we characterize the optimal EM policy based on the solution of an optimization problem. Then, assuming that the power demand profile is known only causally, we obtain the optimal EM policy based on dynamic programming, and also propose a low complexity heuristic policy. For the proposed policies, we characterize the trade-off between user's privacy and energy cost. Finally, we study the delay-constrained linear transmission (LT) of composite Gaussian measurements from a sensor to a CC over a point-to-point fading channel. Assuming that the channel state information (CSI) is known by both the encoder and decoder, we propose the optimal LT strategy in terms of the average mean-square error (MSE) distortion under a strict delay constraint, and two LT strategies under general delay constraints. Assuming that the CSI is known only by the decoder, we propose the optimal LT strategy in terms of the average MSE distortion under a strict delay constraint.La red de energía inteligente (SG) es la mejora de la red eléctrica tradicional. En esta tesis, nos enfocamos en las problemáticas asociadas al diseño de dos de los componentes más críticos de la infraestructura de la SG : los medidores inteligentes (SMs) y las redes de sensores inalámbricos (WSNs). Los SMs miden el consumo de energía de los usuarios y transmiten sus medidas al proveedor de servicio casi en tiempo real. Las medidas de SM permiten la optimización en tiempo real de la gestión de carga en la red. Sin embargo, el posible mal uso de estas medidas plantea preocupaciones graves en cuanto a la privacidad de los usuarios. El desafío es, por lo tanto, diseñar técnicas que puedan aumentar la privacidad de los usuarios manteniendo las capacidades de supervisión que proveen los SMs. Una solución tecnológica es el diseño de sistemas de gestión de energía (EM) inteligentes compuestos por dispositivos de almacenamiento y generación alternativa de energía. Las WSNs se componen de un gran número de sensores, que miden parámetros físicos y transmiten sus mediciones a los centros de control (CCs) mediante enlaces inalámbricos. Los CCs utilizan estas mediciones para estimar el estado del sistema. Para una gestión fiable de la SG, una buena reconstrucción del estado del sistema en tiempo real es crucial. Por ello, es preciso investigar estrategias de transmisión con estrictos requisitos de complejidad y limitaciones de latencia. Para afrontar estos desafíos, esta tesis investiga y diseña técnicas de EM para preservar la privacidad de los usuarios de SM y estrategias de transmisión para WSNs con limitaciones de latencia. Las técnicas de EM propuestas proporcionan privacidad a los consumidores de energía manteniendo los beneficios operacionales para la SG. Las estrategias de transmisión propuestas permiten a las WSNs satisfacer los requisitos de baja latencia necesarios para la reconstrucción precisa del estado en tiempo real; y por lo tanto, la gestión eficiente y robusta de la SG. En primer lugar, consideramos el diseño de un sistema de SM con una unidad de almacenamiento y generación de energía renovable. Representando el sistema con un modelo de estados finitos y de tiempo discreto, proponemos políticas estocásticas de EM. Para las políticas propuestas, caracterizamos la relación fundamental existente entre la privacidad y la eficiencia de energía del usuario, donde la privacidad se mide mediante la tasa de fuga de información y la eficiencia de energía se mide mediante la tasa de energía perdida. En segundo lugar, consideramos el diseño de un sistema de SM con una unidad de almacenamiento. Considerando un modelo de tiempo discreto, estudiamos la relación existente entre la privacidad y el coste de la energía, donde la privacidad se mide por la variación de la carga, así como la información mutua. Suponiendo que el perfil de la demanda de energía y los precios son conocidos de antemano, caracterizamos la política de EM óptima. Suponiendo que la demanda de energía es conocida sólo para el tiempo actual, obtenemos la política de EM óptima mediante programación dinámica, y proponemos una política heurística de baja complejidad. Para las políticas propuestas, caracterizamos la relación existente entre la privacidad y el coste de energía del usuario. Finalmente, consideramos el diseño de estrategias de transmisión lineal (LT) de mediciones Gaussianas compuestas desde un sensor a un CC sobre un canal punto a punto con desvanecimientos. Suponiendo que la información del estado del canal (CSI) es conocida tanto por el trasmisor como por el receptor, proponemos la estrategia de LT óptima en términos de la distorsión de error cuadrático medio (MSE) bajo una restricción de latencia estricta y dos estrategias de LT para restricciones de latencia arbitrarias. Suponiendo que la CSI es conocida sólo en el receptor, proponemos la estrategia de LT óptima en términos de la distorsión de MSE bajo una restricción de latencia estricta.La xarxa d'energia intel·ligent (SG) és la millora de la xarxa elèctrica tradicional. En aquesta tesi, ens enfoquem en les problemàtiques associades al disseny de dos dels components més crítics de la infraestructura de la SG : els mesuradors de consum intel·ligents(SMs) i les xarxes de sensors sense fils (WSNs).Els SMs mesuren el consum d'energia dels usuaris i transmeten les seves mesures al proveïdor de servei gairebé en temps real. Les mesures de SM permeten l'optimització en temps real de la gestió de càrrega a la xarxa. No obstant això, el possible mal ús d'aquestes mesures planteja preocupacions greus en quant a la privacitat dels usuaris. El desafiament és, per tant, dissenyar tècniques que puguin augmentar la privadesa dels usuaris mantenint les capacitats de supervisió que proveeixen els SMs. Una solució tecnològica és el disseny de sistemes de gestió d'energia (EM) intel·ligents compostos per dispositius d'emmagatzematge i generació alternativa d'energia.Les WSNs es componen d'un gran nombre de sensors, que mesuren paràmetres físics i transmeten les seves mesures als centres de control (CCs) mitjançant enllaços sense fils. Els CCs utilitzen aquestes mesures per estimar l'estat del sistema. Per a una gestió fiable de la SG, una bona reconstrucció de l'estat del sistema en temps real és crucial. Per això, cal investigar estratègies de transmissió amb estrictes requisits de complexitat i limitacions de latència. Per d'afrontar aquests desafiaments, aquesta tesi investiga i dissenya tècniques d'EM per preservar la privacitat dels usuaris de SM i estratègies de transmissió per WSNs amb limitacions de latència. Les tècniques d'EM propostes proporcionen privacitats als consumidors d'energia mantenint els beneficis operacionals per la SG. Les estratègies de transmissió proposades permeten a les WSNs satisfer els requisits de baixa latència necessaris per a la reconstrucció precisa de l'estat en temps real; i per tant, la gestió eficient i robusta de la SG.En primer lloc, considerem el disseny d'un sistema de SM amb una unitat d'emmagatzematge i generació d'energia renovable. Representant el sistema amb un model d'estats finits i de temps discret, proposem polítiques estocàstiques d'EM. Per a les polítiques propostes, caracteritzem la relació fonamental existent entre la privadesa i l'eficiència d'energia de l'usuari, on la privacitat es mesura mitjançant la taxa de fugida d'informació i l'eficiència d'energia es mesura mitjançant la taxa d'energia perduda.En segon lloc, considerem el disseny d'un sistema de SM amb una unitat d'emmagatzematge. Considerant un model de temps discret, estudiem la relació existent entre la privacitat el cost de l'energia, on la privacitat es mesura per la variació de la càrrega, així com mitjançant la informació mútua. Suposant que la corba de la demanda d'energia i els preus són coneguts per endavant, caracteritzem la política d'EM òptima. Suposant que la demanda d'energia és coneguda només per al temps actual, obtenim la política d'EM òptima mitjançant programació dinàmica, i proposem una política heurística de baixa complexitat. Per a les polítiques propostes, caracteritzem la relació existent entre la privacitat i el cost d'energia de l'usuari.Finalment, considerem el disseny d'estratègies de transmissió lineal (LT) de mesures Gaussianes compostes des d'un sensor a un CC sobre un canal punt a punt amb esvaïments. Suposant que la informació de l'estat del canal (CSI) és coneguda tant pel transmissor com pel receptor, proposem l'estratègia de LT òptima en termes de la distorsió d'error quadràtic mitjà (MSE) sota una restricció de latència estricta. A més, proposem dues estratègies de LT per a restriccions de latència arbitràries. Finalment, suposant que la CSI és coneguda només en el receptor, proposem l'estratègia de LT òptima en termes de la distorsió de MSE sota una restricció de latència estricta

Entropy in Image Analysis II

Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas

Application and Theory of Multimedia Signal Processing Using Machine Learning or Advanced Methods

This Special Issue is a book composed by collecting documents published through peer review on the research of various advanced technologies related to applications and theories of signal processing for multimedia systems using ML or advanced methods. Multimedia signals include image, video, audio, character recognition and optimization of communication channels for networks. The specific contents included in this book are data hiding, encryption, object detection, image classification, and character recognition. Academics and colleagues who are interested in these topics will find it interesting to read

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Error Resilience in Heterogeneous Visual Communications

A critical and challenging aspect of visual communication technologies is to immunize visual information to transmission errors. In order to effectively protect visual content against transmission errors, various kinds of heterogeneities involved in multimedia delivery need to be considered, such as compressed stream characteristics heterogeneity, channel condition heterogeneity, multi-user and multi-hop heterogeneity. The main theme of this dissertation is to explore these heterogeneities involved in error-resilient visual communications to deliver different visual content over heterogeneous networks with good visual quality. Concurrently transmitting multiple video streams in error-prone environment faces many challenges, such as video content characteristics are heterogeneous, transmission bandwidth is limited, and the user device capabilities vary. These challenges prompt the need for an integrated approach of error protection and resource allocation. One motivation of this dissertation is to develop such an integrated approach for an emerging application of multi-stream video aggregation, i.e. multi-point video conferencing. We propose a distributed multi-point video conferencing system that employs packet division multiplexing access (PDMA)-based error protection and resource allocation, and explore the multi-hop awareness to deliver good and fair visual quality of video streams to end users. When the transport layer mechanism, such as forward error correction (FEC), cannot provide sufficient error protection on the payload stream, the unrecovered transmission errors may lead to visual distortions at the decoder. In order to mitigate the visual distortions caused by the unrecovered errors, concealment techniques can be applied at the decoder to provide an approximation of the original content. Due to image characteristics heterogeneity, different concealment approaches are necessary to accommodate different nature of the lost image content. We address this heterogeneity issue and propose to apply a classification framework that adaptively selects the suitable error concealment technique for each damaged image area. The analysis and extensive experimental results in this dissertation demonstrate that the proposed integrated approach of FEC and resource allocation as well as the new classification-based error concealment approach can significantly outperform conventional error-resilient approaches

Watermarking techniques using knowledge of host database

Ph.DDOCTOR OF PHILOSOPH