Machine Vision

Author:   Wesley E. Snyder (North Carolina State University) ,  Hairong Qi (University of Tennessee, Knoxville)
Publisher:   Cambridge University Press
ISBN:  

9781139168229


Publication Date:   05 June 2012
Format:   Undefined
Availability:   Available To Order   Availability explained
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Machine Vision


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Overview

This 2004 book is an accessible and comprehensive introduction to machine vision. It provides all the necessary theoretical tools and shows how they are applied in actual image processing and machine vision systems. A key feature is the inclusion of many programming exercises that give insights into the development of practical image processing algorithms. The authors begin with a review of mathematical principles and go on to discuss key issues in image processing such as the description and characterization of images, edge detection, restoration and feature extraction, segmentation, texture and shape. They also discuss image matching, statistical pattern recognition, clustering, and syntactic pattern recognition. Important applications are described, including optical character recognition and automatic target recognition. Software and data used in the book can be found at www.cambridge.org/9780521830461. A useful reference for practitioners, the book is aimed at graduate students in electrical engineering, computer science and mathematics.

Full Product Details

Author:   Wesley E. Snyder (North Carolina State University) ,  Hairong Qi (University of Tennessee, Knoxville)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press (Virtual Publishing)
ISBN:  

9781139168229


ISBN 10:   1139168223
Publication Date:   05 June 2012
Audience:   Professional and scholarly ,  Professional and scholarly ,  Professional & Vocational ,  Professional & Vocational
Format:   Undefined
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Table of Contents

1. Introduction; 2. Review of mathematical principles; 3. Writing programs to process images; 4. Images: description and characterization; 5. Linear operators and kernels; 6. Image relaxation: restoration and feature extraction; 7. Mathematical morphology; 8. Segmentation; 9. Shape; 10. Consistent labeling; 11. Parametric transform; 12. Graphs and graph-theoretic concepts; 13. Image matching; 14. Statistical pattern recognition; 15. Clustering; 16. Syntactic pattern recognition; 17. Applications; 18. Automatic target recognition.

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