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Machine Vision: Theory, Algorithms, Practicalities by E. R. Davies — book cover

Machine Vision: Theory, Algorithms, Practicalities

by E. R. Davies
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Overview

"In the last 40 years, machine vision has evolved into a mature field embracing a wide range of applications. While researchers and industry specialists continue to document their work in this area, it has become increasingly difficult for professionals and graduate students to understand the essential theory and practicalities well enough to design their own algorithms and systems. This book directly addresses this need." As in earlier editions, Dr. Davies clearly and systematically presents the basic concepts on the field in highly accessible prose and images, covering essential elements of the theory while emphasizing algorithmic and practical design constraints. In this thoroughly updated edition, he divides the material into horizontal levels of a complete machine vision system. Application case studies demonstrate specific techniques and illustrate key constraints for designing real-world machine vision systems.

In the last 40 years, machine vision has evolved into a mature field embracing a wide range of applications including surveillance, automated inspection, robot assembly, vehicle guidance, traffic monitoring and control, signature verification, biometric measurement, and analysis of remotely sensed images. While researchers and industry specialists continue to document their work in this area, it has become increasingly difficult for professionals and graduate students to understand the essential theory and practicalities well enough to design their own algorithms and systems. This book directly addresses this need.

As in earlier editions, E.R. Davies clearly and systematically presents the basic concepts of the field in highly accessible prose and images, covering essential elements of the theory while emphasizing algorithmic and practical design constraints. In this thoroughly updated edition, he divides the material into horizontal levels of a complete machine vision system. Application case studies demonstrate specific techniques and illustrate key constraints for designing real-world machine vision systems.

About the Author, E. R. Davies

Roy Davies is a Professor of Machine Vision at Royal Holloway, University of London, and has extensive experience of machine vision, image analysis, automated visual inspection, and noise suppression techniques. His book Electronics, Noise, and Signal Recovery was published in 1993 by Academic Press, and is a useful companion to the present volume.

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Editorials

From the Publisher

“This book brings together the analytic aspects of image processing with the practicalities of applying the techniques in an industrial setting. It is excellent grounding for a machine vision researcher.”
— John Billingsley, University of Southern Queensland

“The book in its previous incarnations has established its place as a unique repository of detailed analysis of important image processing and computer vision algorithms.”
— Farzin Deravi, University of Kent

“This book is an essential reference for anyone developing techniques for machine vision analysis, including systems for industrial inspection, biomedical analysis, and much more.”
— Majid Mirmehdi, University of Bristol

“The book contains a large number of experimental design and evaluation procedures that are of keen interest to industrial application engineers of machine vision.”
— William Wee, University of Cincinnati

“Author E.R. Davies covers essential elements of the theory while addressing algorithmic and practical design constraints.”
— Mechanical Engineering, August 2006

Book Details

Published
December 22, 2004
Publisher
Elsevier Science
Pages
934
ISBN
9780080473246

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