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Machine Vision: Algorithms, Architectures, and Systems contains the proceedings of the workshop ""Machine Vision: Where Are We and Where Are We Going?"" sponsored by the Center for Computer Aids for Industrial Productivity (CAIP) at Rutgers University and held in April 1987 in New Brunswick, New Jersey. The papers review the state of the art of machine vision and sets directions for future research. Topics covered include ""smart sensing"" in machine vision, computer architectures for machine vision, and range image segmentation. Comprised of 14 chapters, this book opens with an overview of ""smart sensing"" strategies in machine vision and illustrates how smart sensing may fit into a general purpose vision system by implementing a flexible, modular system called Pipeline Pyramid Machine. The discussion then turns to a hierarchy of local autonomy for processor arrays, focusing on the progression from pure SIMD to complete MIMD as well as the hardware penalties that arise when autonomy is increased. The following chapters explore schemes for integrating vision modules on fine-grained machines; computer architectures for real-time machine vision systems; the application of machine vision to industrial inspection; and characteristics of technologies and social processes that are inhibiting the development and/or evolution of machine vision. Machine vision research at General Motors is also considered. The final chapter assesses future prospects for machine vision and highlights directions for research. This monograph will be a useful resource for practitioners in the fields of computer science and applied mathematics.
'Smart Sensing' in Machine Vision
Introducing Local Autonomy to Processor Arrays
Integrating Vision Modules on a Fine-Grained Parallel Machine
Computer Architectures for Machine Vision
Machine Vision Architectures and Systems — A Discussion
Industrial Machine Vision — Is it Practical?
A Perspective on Machine Vision at General Motors
Industrial Machine Vision: Where are We? What Do We Need? How Do We Get it?
Bottlenecks to Effective Application of Machine Vision — A Discussion
Inference of Object Surface Structure from Structured Lighting — An Overview
Range Image Segmentation
Learning Structural Descriptions of Shape
Machine Vision as State-Space Search
Directions for Future Research - A Panel Discussion
- No. of pages:
- © Academic Press 1988
- 28th April 1988
- Academic Press
- eBook ISBN:
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