You may have to register before you can download all our books and magazines, click the sign up button below to create a free account.
Over the past few years, the demand for high speed Digital Signal Proces sing (DSP) has increased dramatically. New applications in real-time image processing, satellite communications, radar signal processing, pattern recogni tion, and real-time signal detection and estimation require major improvements at several levels; algorithmic, architectural, and implementation. These perfor mance requirements can be achieved by employing parallel processing at all levels. Very Large Scale Integration (VLSI) technology supports and provides a good avenue for parallelism. Parallelism offers efficient sohitions to several problems which can arise in VLSI DSP architectures such as: 1. Intermediate data ...
Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge representation in semantic networks, production rules, mechanization of logic, constraint satisfaction, parsing of natural language, data filtering and data mining. The publication is divided into six sections. The first addresses parallel computing for processing and understanding images. The second discusses parallel processing for semantic networks, which are widely used means for representing knowledge...
Recent research results in the area of parallel algorithms for problem solving, search, natural language parsing, and computer vision, are brought together in this book. The research reported demonstrates that substantial parallelism can be exploited in various machine intelligence and vision problems. The chapter authors are prominent researchers actively involved in the study of parallel algorithms for machine intelligence and vision. Extensive experimental studies are presented that will help the reader in assessing the usefulness of an approach to a specific problem. Intended for students and researchers actively involved in parallel algorithms design and in machine intelligence and vision, this book will serve as a valuable reference work as well as an introduction to several research directions in these areas.
This book presents reports by well-known experts on the most recent research results in image coding, analysis and understanding, and promising applications for solving real problems in manufacturing, remote sensing and biomedicine. The topics covered include shape analysis and computer vision, pattern recognition methods and applications, parallel computer architectures for image processing and analysis, human perception and use of artificial intelligence techniques for image understanding, languages for image abstraction, processing and retrieval, vision modules and neural computation.
Dynamic Reconfiguration: Architectures and Algorithms offers a comprehensive treatment of dynamically reconfigurable computer architectures and algorithms for them. The coverage is broad starting from fundamental algorithmic techniques, ranging across algorithms for a wide array of problems and applications, to simulations between models. The presentation employs a single reconfigurable model (the reconfigurable mesh) for most algorithms, to enable the reader to distill key ideas without the cumbersome details of a myriad of models. In addition to algorithms, the book discusses topics that provide a better understanding of dynamic reconfiguration such as scalability and computational power, and more recent advances such as optical models, run-time reconfiguration (on FPGA and related platforms), and implementing dynamic reconfiguration. The book, featuring many examples and a large set of exercises, is an excellent textbook or reference for a graduate course. It is also a useful reference to researchers and system developers in the area.
The papers in this volume focus on the most modern and critical aspects of Image and Signal Processing and related areas that have a significant impact in our society. The papers may be categorized in the following four major parts. Coding and Compression (image coding, image subband, wavelet coding and representation, video coding, motion estimation and multimedia); Image Processing and Pattern Recognition (image analysis, edge detection, segmentation, image enhancement and restoration, adaptive systems, colour processing, pattern and object recognition and classification); Fast Processing Techniques (computational methods, VLSI DSP architectures); Theory and Applications (identificiation and modelling, multirate filter banks, wavelets in image and signal processing, biomedical and industrial applications). The authors of these exceptionally high-quality papers form an interesting group, originating from the five continents, representing 33 countries.
This is the proceedings of the SIGAL International Symposium on Algorithms held at CSK Information Education Center, Tokyo, Japan, August 16-18, 1990. SIGAL (Special Interest Group on Algorithms) was organized within the Information Processing Society of Japan in 1988 to encourage research in the field of discrete algorithms, and held 6-8 research meetings each year. This symposium is the first international symposium organized by SIGAL. In response to the call for papers, 88 papers were submitted from around the world. The program committee selected 34 for presentation at the symposium. The symposium also included 5 invited lectures and 10 invited presentations. The subjects of the papers range widely in the field of discrete algorithms in theoretical computer science. Keywords for these subjects are: computational geometry, graph algorithms, complexity theory, parallel algorithms, distributed computing, and computational algebra.
Image Processing, Analysis and Machine Vision represent an exciting part of modern cognitive and computer science. Following an explosion of inter est during the Seventies, the Eighties were characterized by the maturing of the field and the significant growth of active applications; Remote Sensing, Technical Diagnostics, Autonomous Vehicle Guidance and Medical Imaging are the most rapidly developing areas. This progress can be seen in an in creasing number of software and hardware products on the market as well as in a number of digital image processing and machine vision courses offered at universities world-wide. There are many texts available in the areas we cover - most (indeed, all of ...
Advances in microelectronic technology have made massively parallel computing a reality and triggered an outburst of research activity in parallel processing architectures and algorithms. Distributed memory multiprocessors - parallel computers that consist of microprocessors connected in a regular topology - are increasingly being used to solve large problems in many application areas. In order to use these computers for a specific application, existing algorithms need to be restructured for the architecture and new algorithms developed. The performance of a computation on a distributed memory multiprocessor is affected by the node and communication architecture, the interconnection network ...