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.

Table of Contents:
1.1 VLSI System.- 1.2 VLSI Algorithms.- 1.3 Summary of Book.- References.- I General VLSI Design Considerations.- 2. One-Dimensional Systolic Arrays for Multidimensional Convolution and Resampling.- 2.1 Background.- 2.2 Systolic Convolution Arrays.- 2.3 Variants in the Convolution Problem.- 2.4 Implementation.- 2.5 Concluding Remarks.- References.- 3. VLSI Arrays for Pattern Recognition and Image Processing: I/O Bandwidth Considerations.- 3.1 Background.- 3.2 Arrays for Matrix Operations.- 3.3 Arrays for Pattern Analysis.- 3.4 Image-Processing Array.- 3.5 Conclusions.- References.- II VLSI Systems for Pattern Recognition.- 4. VLSI Arrays for Minimum-Distance Classifications.- 4.1 Minimum-Distance Classification.- 4.2 Vector Distances.- 4.3 String Distances.- 4.4 Examples of Application.- 4.5 Summary.- References.- 5. Design of a Pattern Cluster Using Two-Level Pipelined Systolic Array.- 5.1 Background.- 5.2 Description of Squared-Error Pattern Clustering.- 5.3 The Systolic Pattern Clustering Array.- 5.4 System Operating Characteristics.- 5.5 Conclusion.- References.- 6. VLSI Arrays for Syntactic Pattern Recognition.- 6.1 Pattern Description and Recognition.- 6.2 Syntactic Pattern Recognition.- 6.3 VLSI Implementation.- 6.4 Simulation and Examples.- 6.5 Concluding Remarks.- References.- III VLSI Systems for Image Processing.- 7. Concurrent Systems for Image Analysis.- 7.1 Background.- 7.2 Processing Requirements for Image Analysis.- 7.3 Concurrent VLSI Architectures.- 7.4 Conclusions.- References.- 8. VLSI Wavefront Arrays for Image Processing.- 8.1 Background.- 8.2 Parallel Computers for Image Processing.- 8.3 Design of Pipelined Array Processors.- 8.4 Image-Processing Applications.- 8.5 Wafer-Scale Integrated System.- 8.6 Conclusion.- References.- 9. Curve Detection in VLSI.- 9.1 Background.- 9.2 Montanari's Algorithm.- 9.3 Systolic Architectures.- 9.4 A VLSI Design of the Column Pipeline Chip.- 9.5 SIMD Array Algorithm.- 9.6 Concluding Remarks.- References.- 10. VLSI Implementation of Cellular Logic Processors.- 10.1 Cellular Logic Processors.- 10.2 Binary Neighborhood Functions.- 10.3 CELLSCAN.- 10.4 The Golay Parallel Pattern Transform.- 10.5 The diff3-GLOPR.- 10.6 The Preston-Herron Processor (PHP).- 10.7 The LSI/PHP.- References.- 11. Design of VLSI Based Multicomputer Architecture for Dynamic Scene Analysis.- 11.1 Background.- 11.2 Dynamic Scene Analysis Algorithm.- 11.3 Existing Multicomputer Architecture.- 11.4 Scheduling and Parameters of Interest.- 11.5 Performance Evaluation.- 11.6 Conclusion.- References.- 12. VLSI-Based Image Resampling for Electronic Publishing.- 12.1 Introduction to the "Electronic Darkroom".- 12.2 Overview of System Design Concepts.- 12.3 Resampling Algorithms.- 12.4 System Architecture and Performance.- 12.5 Trade-Offs and Conclusions.- References.