Machine Vision: Theory, Algorithms, Practicalities / Edition 2

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Overview

The field of machine vision has expanded extensively since the First Edition of Machine Vision was published by Academic Press in 1990. As a result, this Second Edition contains significant amounts of new material on artificial neural networks, mathematical morphology, motion, invariance, texture analysis, x-ray inspection, and foreign object detection. Intermediate level vision is examined in depth (especially Hough transforms), and automated visual inspectionis discussed. The author takes care to consider theoretical aspects as well as practical applications, including perspective invariants and robust statistics. Written in a user-friendly style and full of up-to-date methods, Machine Vision, Second Edition will be an essential volume for students and professionals in the field.

Key Features
* Gives considerable emphasis to robust analysis of images to demonstrate how problems of occlusion, noise, distortion, and variability may be overcome
* Introduces Hough transforms as an integral part of the text and shows how they may be applied in a variety of situations
* Presents the topic of robust statistics non-mathematically in the context of vision algorithms
* Considers the role of neural networks in machine vision
* Shows how the concepts of perspective invariance provide basic strategies for 2-D and 3-D vision
* Studies image transformations and the prespective n-point problem systematically to clarify how interpretation may proceed in various geometrical situations
* Pays special attention to the detection of defects, foreign objects, and real-time implementation hardware in consideration of automated visual inspection

The field of machine vision has expanded extensively since the First Edition of Machine Vision was published by Academic Press in 1990. As a result, this Second Edition contains significant amounts of new material on artificial neural networks, mathematical morphology, motion, invariance, texture analysis, x-ray inspection, and foreign object detection. Intermediate level vision is examined in depth (especially Hough transforms), and automated visual inspectionis discussed. The author takes care to consider theoretical aspects as well as practical applications, including perspective invariants and robust statistics. Written in a user-friendly style and full of up-to-date methods, Machine Vision, Second Edition will be an essential volume for students and professionals in the field.

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Product Details

  • ISBN-13: 9780122060922
  • Publisher: Elsevier Science & Technology Books
  • Publication date: 1/28/1997
  • Series: Signal Processing and Its Applications Series
  • Edition description: Older Edition
  • Edition number: 2
  • Pages: 750
  • Product dimensions: 5.94 (w) x 9.04 (h) x 1.36 (d)

Table of Contents

Preface to First Edition
Preface to Second Edition
About the Author
Glossary of Acronyms and Abbreviations
Acknowledgements
1 Vision, the Challenge 1
2 Images and Imaging Operations 19
3 Basic Image Filtering Operations 41
4 Thresholding Techniques 79
5 Locating Objects via Their Edges 103
6 Binary Shape Analysis 131
7 Boundary Pattern Analysis 171
8 Line Detection 195
9 Circle Detection 211
10 The Hough Transform and Its Nature 245
11 Ellipse Detection 271
12 Hole Detection 291
13 Polygon and Corner Detection 309
14 Abstract Pattern Matching Techniques 347
15 The Three-Dimensional World 373
16 Tackling the Perspective N-Point Problem 417
17 Motion 431
18 Invariants and Their Applications 455
19 Automated Visual Inspection 471
20 Statistical Pattern Recognition 503
21 Biologically Inspired Recognition Schemes 529
22 Texture 561
23 Image Acquisition 583
24 The Need for Speed: Real-Time Electronic Hardware Systems 603
25 Machine Vision, Art or Science? 623
App. A Programming Notation 635
App. B Mathematical Morphology 647
App. C Image Transformations and Camera Calibration 663
App. D Robust statistics 677
References 695
Subject Index 725
Author Index 741
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