Vlsi For Pattern Recognition And Image Processing

During the past two decades there has been a considerable growth in interest in problems of pattern recognition and image processing (PRIP). This inter est has created an increasing need for methods and techniques for the design of PRIP systems. PRIP involves analysis, classification and interpretation of data. Practical applications of PRIP include character recognition, re mote sensing, analysis of medical signals and images, fingerprint and face identification, target recognition and speech understanding. One difficulty in making PRIP systems practically feasible, and hence, more popularly used, is the requirement of computer time and storage. This situation is particularly serious when the patterns to be analyzed are quite complex. Thus it is of the utmost importance to investigate special comput er architectures and their implementations for PRIP. Since the advent of VLSI technology, it is possible to put thousands of components on one chip. This reduces the cost of processors and increases the processing speed. VLSI algorithms and their implementations have been recently developed for PRIP. This book is intended to document the recent major progress in VLSI system design for PRIP applications.

This book covers parallel algorithms and architectures and VLSI chips for a range of problems in image processing, computer vision, pattern recognition and artificial intelligence. The specific problems addressed include vision and image processing tasks, Fast Fourier Transforms, Hough Transforms, Discrete Cosine Transforms, image compression, polygon matching, template matching, pattern matching, fuzzy expert systems and image rotation. The collection of papers gives the reader a good introduction to the state-of-the-art, while for an expert this serves as a good reference and a source of some new contributions in this field. Contents:ENPASSANT: An Environment for Evaluating Massively Parallel Array Architectures for Spatially Mapped Applications (M C Herbordt & C C Weems)A Reconfigurable Architecture for Image Processing and Computer Vision (S M Bhandarkar et al.)A Design Methodology for Very Large Array Processors — Part 1: GIPOP Processor Array (N Venkateswaran et al.)A Design Methodology for Very Large Array Processors — Part 2: PACUBE VLSI Arrays (N Venkateswaran et al.)A VLSI Implementation of Inverse Discrete Cosine Transform (A K Bhattacharya & S S Haider)Systolic Merging and Ranking of Votes for the Generalized Hough Transform (M Albanesi & M Ferretti)High Speed Parallel VLSI Architectures for Image Decorrelation (T Acharya & A Mukherjee)PMAC: A Polygon Matching Chip (R Sastry & N Ranganathan)Quadtree Algorithms for Template Matching on Mesh Connected Computer (H Senoussi & A Saoudi)Fast Pattern-Matching Algorithm on Modular Mesh-Connected Computers with Multiple Buses (K L Chung)A VLSI Parallel Architecture for Fuzzy Expert Systems (V Catania & G Ascia)VLSI Implementation of an Efficient ASIC Architecture for Real-Time Rotation of Digital Images (I Ghosh & B Majumdar) Readership: Computer scientists and electrical engineers. keywords:

This book covers parallel algorithms and architectures and VLSI chips for a range of problems in image processing, computer vision, pattern recognition and artificial intelligence. The specific problems addressed include vision and image processing tasks, Fast Fourier Transforms, Hough Transforms, Discrete Cosine Transforms, image compression, polygon matching, template matching, pattern matching, fuzzy expert systems and image rotation. The collection of papers gives the reader a good introduction to the state-of-the-art, while for an expert this serves as a good reference and a source of some new contributions in this field.

This book delivers a course module for advanced undergraduates, postgraduates and researchers of electronics, computing science, medical imaging, or wherever the study of identification and classification of objects by electronics-driven image processing and pattern recognition is relevant. Object analysis first uses image processing to detect objects and extract their features, then identifies and classifies them by pattern recognition. Its manifold applications include recognition of objects in satellite images which enable discrimination between different objects, such as fishing boats, merchant ships or warships; machine spare parts e.g. screws, nuts etc. (engineering); detection of cancers, ulcers, tumours and so on (medicine); and recognition of soil particles of different types (agriculture or soil mechanics in civil engineering). Outlines the identification and classification of objects by electronics-driven image processing and pattern recognition Discusses object detection, shape, roundness and sharpness analysis, orientation analysis and arrangement analysis Delivers a course module for advanced undergraduates, postgraduates and researchers of electronics, computing science and medical imaging

The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.

This volume provides a collection of sixteen articles containing review and new material. In a unified way, they describe the recent development of theories and methodologies in pattern recognition, image processing and vision using fuzzy logic, artificial neural networks, genetic algorithms, rough sets and wavelets with significant real life applications.The book details the theory of granular computing and the role of a rough-neuro approach as a way of computing with words and designing intelligent recognition systems. It also demonstrates applications of the soft computing paradigm to case based reasoning, data mining and bio-informatics with a scope for future research.The contributors from around the world present a balanced mixture of current theory, algorithms and applications, making the book an extremely useful resource for students and researchers alike.

This practical handbook provides a broad overview of the major elements of pattern recognition and image processing (PRIP). Currently the only handbook in the field, it is designed as a source of "quick answers" for those interested in the theoretical development and practical applications of PRIP techniques. Twenty years of research, development, and innovations in applications are documented in this comprehensive work. Written by leading researchers in the field, chapters deal with statistical and syntactic pattern recognition feature selection and extraction cluster analysis image enhancement and restoration shapes, texture, and motion computer vision computer systems and architectures for image processing and various industrial and biomedical applications. Engineers, computer scientists, other professionals, and students interested in applying PRIP techniques will find the Handbook of Pattern Recognition and Image Processing to be an invaluable reference source.