Machine Vision. Algorithms, Architectures, and Systems

✍ Scribed by Herbert Freeman (Eds.)

Publisher: Academic Press
Year: 1988
Tongue: English
Leaves: 318
Series: Perspectives in computing (Boston, Mass.), vol. 20
Category: Library

No coin nor oath required. For personal study only.

✦ Table of Contents

Content:
Front Inside Cover, Page ii
Front Matter, Page iii
Copyright, Page iv
Preface, Pages vii-viii, Herbert Freeman
Contributors, Pages ix-x
‘Smart Sensing’ in Machine Vision, Pages 1-30, Peter J. Burt
Introducing Local Autonomy to Processor Arrays, Pages 31-56, T.J. Fountain
Integrating Vision Modules on a Fine-Grained Parallel Machine, Pages 57-96, James J. Little
Computer Architectures for Machine Vision, Pages 97-101, Azriel Rosenfeld
Machine Vision Architectures and Systems — A Discussion, Pages 103-107, T.J. Fountain
Industrial Machine Vision — Is It Practical?, Pages 109-148, Joseph L. Mundy
A Perspective on Machine Vision at General Motors, Pages 149-159, Wayne Wiitanen
Industrial Machine Vision: Where Are We? What Do We Need? How Do We Get It?, Pages 161-185, Mark A. Lavin
Bottlenecks to Effective Application of Machine Vision — A Discussion, Pages 187-192, J. Sklansky
Inference of Object Surface Structure from Structured Lighting — An Overview, Pages 193-220, J.K. Aggarwal, Y.F. Wang
Range Image Segmentation, Pages 221-256, Paul J. Besl, Ramesh C. Jain
Learning Structural Descriptions of Shape, Pages 257-271, Jakub Segen
Machine Vision as State-Space Search, Pages 273-298, Steven L. Tanimoto
Directions for Future Research — A Panel Discussion, Pages 299-309, Herbert Freeman, J.K. Aggarwal, Nelson R. Corby, John Jarvis, Steven Tanimoto, Wayne Wiitanen
Index, Pages 311-315
Perspectives in Computing, Pages 317-318

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