Machine Vision : Theory, Algorithms, Practicalities

by Davies, E. R.

• ISBN13: 9780122060908
• ISBN10: 0122060903
• eBook ISBN(s): 9781483275611
• Format: Hardcover
• Copyright: 1991-01-01
• Publisher: Academic Pr
• More Book Details
• Purchase Benefits

Summary

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. Includes solid, accessible coverage of 2-D and 3-D scene analysis. Offers thorough treatment of the Hough Transforma key technique for inspection and surveillance. Brings vital topics and techniques together in an integrated system design approach. Takes full account of the requirement for real-time processing in real applications.

Table of Contents

Vision, the Challenge

Low-Level Processing: Images and Imaging Operations

Basic Image Filtering Operations

Thresholding Techniques

Locating Objects via Their Edges

Binary Shape Analysis

Boundary Pattern Analysis

Intermediate-Level Processing: Line Detection

Circle Detection

The Hough Transform and Its Nature

Ellipse Detection

Hole Detection

Polygon and Corner Detection

Application Level Processing: Abstract Pattern Matching Techniques

The Three-Dimensional World

Tackling the Perspective n-Point Problem

Motion

Invariants and their Applications

Automated Visual Inspection

Statistical Pattern Recognition

Biologically Inspired Recognition Schemes

Texture

Image Acquisition

The Need for Speed: Real-Time Electronic Hardware Systems

Perspectives on Vision: Machine Vision, Art or Science?

Appendices

References

Subject Index

Author Index

Vision, the Challenge: Introduction

Man and his Senses

The Nature of Vision

Automated Visual Inspection

What This Book is About

The Following Chapters

Low-Level Processing: Images and Imaging Operations: Image Processing Operations

Convolutions and Point Spread Functions

Sequential Versus Parallel Operations

Basic Image Filtering Operations: Noise Suppression by Gaussian Smoothing

Median Filtering

Mode Filtering

Bias Generated by Noise Suppression Filters

Reducing Computational Load

The Role of Filters in Industrial Applications of Vision

Sharp-Unsharp Masking

Thresholding Techniques: Region-Growing Methods

Thresholding

Adaptive Thresholding

Locating Objects via Their Edges: Basic Theory of Edge Detection

The Template Matching Approach

Theory of 3 x 3 Template Operators

Summary

Design Constraints and Conclusions

The Design of Differential Gradient Operators

The Concept of a Circular Operator

Detailed Implementation of Circular Operators

Structured Bands of Pixels in Neighbourhoods of Various Sizes

The Systematic Design of Differential Edge Operators

Problems with the Above ApproachSome Alternative Schemes

Binary Shape Analysis: Connectedness in Binary Images

ObjectLabelling and Counting

Metric Properties in Digital Images

Size Filtering

The Convex Hull and Its Computation

Distance Functions and Their Uses

Skeletons and Thinning

Some Simple Measures for Shape Recognition

Shape Description by Moments

BoundaryTracking Procedures

Boundary Pattern Analysis: Boundary Tracking Procedures

Template Matchinga Reminder

Centroidal Profiles

Problems with the Centroidal Profile Approach

The (s, () Plot

Tackling the Problems of Occlusion

Chain Code

The (r, s) Plot

Accuracy of Boundary Length Measures

Concluding Remarks

Bibliographical and Historical

Notes

Intermediate-Level Processing: Line Detection: Application of the Hough Transform to Line Detection

The Foot-of-Normal Method

Longitudinal Line Localization

Final Line Fitting

Circle Detection: Hough-Based Schemes for Circular Object Detection

The Problem of Unknown Circle Radius

The Problem of Accurate Centre Location

Overcoming the Speed Problem

The Hough Transform and Its Nature: The Generalized Hough Transform

Setting Up the Generalized Hough TransformSome Relevant Questions

Spatial Matched Filtering in Images

From Spatial Matched Filters to Generalized Hough Transforms

Gradient Weighting Versus Uniform Weighting

Summary

Applying the Generalized Hough Transform to Line Detection

An Instructive Example

Tradeoffs to Reduce Computational Load

The Effects of Occlusions for Objects with Straight Edges

Fast Implementations of the HoughTransform

The Approach of Gerig and Klein

Ellipse Detection: The Diameter Bisection Method

The Chord Tangent Method

Finding the Remaining Ellipse Parameters

Reducing Computational Load for the Generalized Hough Transform Method

Comparing the Various Methods

Hole Detection: The Template Matching Approach

The Lateral Histogram Technique

The Removal of Ambiguities in the Lateral Histrogram

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