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There are six sections in this book. The first section presents basic image processing techniques, such as image acquisition, storage, retrieval, transformation, filtering, and parallel computing. Then, some applications, such as road sign recognition, air quality monitoring, remote sensed image analysis, and diagnosis of industrial parts are considered. Subsequently, the application of image processing for the special eye examination and a newly three-dimensional digital camera are introduced. On the other hand, the section of medical imaging will show the applications of nuclear imaging, ultrasound imaging, and biology. The section of neural fuzzy presents the topics of image recognition, self-learning, image restoration, as well as evolutionary. The final section will show how to implement the hardware design based on the SoC or FPGA to accelerate image processing.
This book describes the prize-winning brain-computer-interface (BCI) projects honored in the community's most prestigious annual award. BCIs enable people to communicate and control their limbs and/or environment using thought processes alone. Research in this field continues to develop and expand rapidly, with many new ideas, research groups, and improved technologies having emerged in recent years. The chapters in this volume feature the newest developments from many of the best labs worldwide. They present both non-invasive systems (based on the EEG) and intracortical methods (based on spikes or ECoG), and numerous innovative applications that will benefit new user groups
This work is a comprehensive study of the field. It provides an entry point to the novice willing to move in the research field reconfigurable computing, FPGA and system on programmable chip design. The book can also be used as teaching reference for a graduate course in computer engineering, or as reference to advance electrical and computer engineers. It provides a very strong theoretical and practical background to the field, from the early Estrin’s machine to the very modern architecture such as embedded logic devices.
This book summarizes the key scientific outcomes of the Horizon 2020 research project TULIPP: Towards Ubiquitous Low-power Image Processing Platforms. The main focus lies on the development of high-performance, energy-efficient embedded systems for the growing range of increasingly complex image processing applications. The holistic TULIPP approach is described in the book, which addresses hardware platforms, programming tools and embedded operating systems. Several of the results are available as open-source hardware/software for the community. The results are evaluated with several use cases taken from real-world applications in key domains such as Unmanned Aerial Vehicles (UAVs), robotics, space and medicine. Discusses the development of high-performance, energy-efficient embedded systems for the growing range of increasingly complex image processing applications; Covers the hardware architecture of embedded image processing systems, novel methods, tools and libraries for programming those systems as well as embedded operating systems to manage those systems; Demonstrates results with several challenging applications, such as medical systems, robotics, drones and automotive.
The Fourier transform is one of the most fundamental tools for computing the frequency representation of signals. It plays a central role in signal processing, communications, audio and video compression, medical imaging, genomics, astronomy, as well as many other areas. Because of its widespread use, fast algorithms for computing the Fourier transform can benefit a large number of applications. The fastest algorithm for computing the Fourier transform is the Fast Fourier Transform (FFT), which runs in near-linear time making it an indispensable tool for many applications. However, today, the runtime of the FFT algorithm is no longer fast enough especially for big data problems where each dataset can be few terabytes. Hence, faster algorithms that run in sublinear time, i.e., do not even sample all the data points, have become necessary. This book addresses the above problem by developing the Sparse Fourier Transform algorithms and building practical systems that use these algorithms to solve key problems in six different applications: wireless networks; mobile systems; computer graphics; medical imaging; biochemistry; and digital circuits. This is a revised version of the thesis that won the 2016 ACM Doctoral Dissertation Award.
This book presents an overview of the guidelines and strategies for transitioning an image or video processing algorithm from a research environment into a real-time constrained environment. Such guidelines and strategies are scattered in the literature of various disciplines including image processing, computer engineering, and software engineering, and thus have not previously appeared in one place. By bringing these strategies into one place, the book is intended to serve the greater community of researchers, practicing engineers, industrial professionals, who are interested in taking an image or video processing algorithm from a research environment to an actual real-time implementation on a resource constrained hardware platform. These strategies consist of algorithm simplifications, hardware architectures, and software methods. Throughout the book, carefully selected representative examples from the literature are presented to illustrate the discussed concepts. After reading the book, the readers are exposed to a wide variety of techniques and tools, which they can then employ to design a real-time image or video processing system.
The book is designed for end users in the field of digital imaging, who wish to update their skills and understanding with the latest techniques in image analysis. The book emphasizes the conceptual framework of image analysis and the effective use of image processing tools. It uses applications in a variety of fields to demonstrate and consolidate both specific and general concepts, and to build intuition, insight and understanding. Although the chapters are essentially self-contained they reference other chapters to form an integrated whole. Each chapter employs a pedagogical approach to ensure conceptual learning before introducing specific techniques and “tricks of the trade”. The book concentrates on a number of current research applications, and will present a detailed approach to each while emphasizing the applicability of techniques to other problems. The field of topics is wide, ranging from compressive (non-uniform) sampling in MRI, through automated retinal vessel analysis to 3-D ultrasound imaging and more. The book is amply illustrated with figures and applicable medical images. The reader will learn the techniques which experts in the field are currently employing and testing to solve particular research problems, and how they may be applied to other problems.
This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications.