3D Wavelet Transformation for Visual Data Coding With Spatio and Temporal Scalability as Quality Artifacts: Current State Of The Art

Several techniques based on the three–dimensional (3-D) discrete cosine transform (DCT) have been proposed for visual data coding. These techniques fail to provide coding coupled with quality and resolution scalability, which is a significant drawback for contextual domains, such decease diagnosis, satellite image analysis. This paper gives an overview of several state-of-the-art 3-D wavelet coders that do meet these requirements and mainly investigates various types of compression techniques those exists, and putting it all together for a conclusion on further research scope

A real-time multi-sensor 3D surface shape measurement system using fringe analysis

This thesis presents a state-of-the-art multi-sensor, 3D surface shape measurement system that is based upon fringe projection/analysis and which operates at speeds approaching real-time. The research programme was carried out as part of MEGURATH (www.megurath.org), a collaborative research project with the aim of improving the treatment of cancer by radiotherapy. The aim of this research programme was to develop a real-time, multi-sensor 3D surface shape measurement system that is based on fringe analysis, which provides the flexibility to choose from amongst several different fringe profilometry methods and to manipulate their settings interactively. The system has been designed specifically to measure dynamic 3D human body surface shape and to act as an enabling technology for the purpose of performing Metrology Guided Radiotherapy (MGRT). However, the system has a wide variety of other potential applications, including 3D modelling and visualisation, verbatim replication, reverse engineering and industrial inspection. It can also be used as a rapid prototyping tool for algorithm development and testing, within the field of fringe pattern profilometry. The system that has been developed provides single, or multi-sensor, measurement modes that are adaptable to the specific requirements of a desired application. The multi-sensor mode can be useful for covering a larger measurement area, by providing a multi-viewpoint measurement. The overall measurement accuracy of the system is better than O.5mm, with measurement speeds of up to 3 million XYZ points/second using the single-sensor mode and rising to up to 4.6 million XYZ points/second when measuring in parallel using the three sensor multi-sensor mode. In addition the system provides a wide-ranging catalogue of fringe profilometry methods and techniques, that enables the reconstruction of 3D information through an interactive user selection of 183 possible different paths of main combinations. The research aspects behind the development of the system are presented in this thesis, along with the author's contribution to this field of research, which has included the provision of a comprehensive framework for producing such a novel optical profilometry system, and the specific techniques that were developed to fulfil the aims of this research programme. This mainly included the following advanced methods: a transversal calibration method for the optical system, an adaptive filtering technique for the Fourier Transform Profilometry (FTP) method, and a method to synthetically restore the locations of the triangulation spots. Similarly, potential applications for the system have been presented and feasibility and accuracy analyses have been conducted, presenting both qualitative and quantitative measurement results. To this end, the high robustness levels exhibited by the system have been demonstrated (in terms of adaptability, accuracy and measurement capability) by performing extensive real experiments and laboratory testing. Finally, a number of potential future system developments are described, with the intention of further extending the system capabilities

Applications in Electronics Pervading Industry, Environment and Society

This book features the manuscripts accepted for the Special Issue “Applications in Electronics Pervading Industry, Environment and Society—Sensing Systems and Pervasive Intelligence” of the MDPI journal Sensors. Most of the papers come from a selection of the best papers of the 2019 edition of the “Applications in Electronics Pervading Industry, Environment and Society” (APPLEPIES) Conference, which was held in November 2019. All these papers have been significantly enhanced with novel experimental results. The papers give an overview of the trends in research and development activities concerning the pervasive application of electronics in industry, the environment, and society. The focus of these papers is on cyber physical systems (CPS), with research proposals for new sensor acquisition and ADC (analog to digital converter) methods, high-speed communication systems, cybersecurity, big data management, and data processing including emerging machine learning techniques. Physical implementation aspects are discussed as well as the trade-off found between functional performance and hardware/system costs

Data Hiding and Its Applications

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others

A Flexible, Low-Power, Programmable Unsupervised Neural Network Based on Microcontrollers for Medical Applications

We present an implementation and laboratory tests of a winner takes all (WTA) artificial neural network (NN) on two microcontrollers (μC) with the ARM Cortex M3 and the AVR cores. The prospective application of this device is in wireless body sensor network (WBSN) in an on-line analysis of electrocardiograph (ECG) and electromyograph (EMG) biomedical signals. The proposed device will be used as a base station in the WBSN, acquiring and analysing the signals from the sensors placed on the human body. The proposed system is equiped with an analog-todigital converter (ADC), and allows for multi-channel acquisition of analog signals, preprocessing (filtering) and further analysis

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts