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Machine Vision

Machine Vision

Theory, Algorithms, Practicalities

E. R. Davies

950 pages, parution le 31/01/2005 (3eme édition)

Résumé

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.

L'auteur - E. R. Davies

E. R. Davies: Royal Holloway, University of London, U.K.

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.

Sommaire

  • Low-Level Vision
  • Intermediate-Level vision
  • 3-d Vision and Motion
  • Toward Real-Time Pattern Recognition Systems
  • Perspectives on Vision
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Caractéristiques techniques

  PAPIER
Éditeur(s) Morgan Kaufmann
Auteur(s) E. R. Davies
Parution 31/01/2005
Édition  3eme édition
Nb. de pages 950
Format 20 x 24
Couverture Relié
Poids 2080g
Intérieur Noir et Blanc
EAN13 9780122060939
ISBN13 978-0-12-206093-9

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