Machine Vision: Theory, Algorithms, Practicalities
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 Transform—a 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.
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Machine Vision: Theory, Algorithms, Practicalities
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 Transform—a 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.
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Machine Vision: Theory, Algorithms, Practicalities

Machine Vision: Theory, Algorithms, Practicalities

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

Machine Vision: Theory, Algorithms, Practicalities

by E. R. Davies

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$109.00 

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Overview

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 Transform—a 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.

Product Details

ISBN-13: 9780080473246
Publisher: Morgan Kaufmann Publishers
Publication date: 12/22/2004
Series: Signal Processing and its Applications
Sold by: Barnes & Noble
Format: eBook
Pages: 934
File size: 23 MB
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About the Author

Roy Davies was Emeritus Professor of Machine Vision at Royal Holloway, University of London. He worked on many aspects of vision, from feature detection to robust, real-time implementations of practical vision tasks. His interests included automated visual inspection, surveillance, vehicle guidance, crime detection and neural networks. He has published more than 200 papers, and three books. Machine Vision: Theory, Algorithms, Practicalities (1990) has been widely used internationally for more than 25 years, and is now out in this much enhanced fifth edition. Roy held a DSc at the University of London and was awarded Distinguished Fellow of the British Machine Vision Association, and Fellow of the International Association of Pattern Recognition.

Table of Contents

1. Vision, the ChallengePart 1 Low-Level Vision2. Images and Imaging Operations3. Basic Image Filtering Operations4. Thresholding Techniques5. Edge Detection6. Binary Shape Analysis7. Boundary Pattern Analysis8. Mathematical MorphologyPart 2 Intermediate-Level Vision9. Line Detection10. Circle Detection11. The Hough Transform and Its Nature12. Ellipse Detection13. Hole Detection14. Polygon and Corner Detection15. Abstract Pattern Matching TechniquesPart 3 3–D Vision and Motion16. The Three-Dimensional World17. Tackling the Perspective n-Point Problem18. Motion19. Invariants and their Applications20. Egomotion and Related Tasks21. Image Transformations and Camera CalibrationPart 4 Towards Real-Time Pattern Recognition Systems22. Automated Visual Inspection23. Inspection of Cereal Grains24. Statistical Pattern Recognition25. Biologically Inspired Recognition Schemes26. Texture27. Image Acquisition28. Real-Time Hardware and Systems Design ConsiderationsPart 5 Perspectives on Vision29. Machine Vision, Art or Science?Appendix A Robust Statistics

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Thoroughly updated solid text reference for an increasingly important field

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