Editors:
- Presents the latest technologies and solutions for industrial inspection
- Covers both theoretical advances and current engineering practices
- Includes case studies that illustrate applications of the techniques to real problems
- Includes supplementary material: sn.pub/extras
Part of the book series: Advances in Computer Vision and Pattern Recognition (ACVPR)
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Table of contents (15 chapters)
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Front Matter
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Technology Advances
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Front Matter
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Applications and System Integration for Vision-Based Inspection
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Front Matter
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Back Matter
About this book
Editors and Affiliations
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University of British Columbia, Kelowna, Canada
Zheng Liu
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University of Tokushima, Tokushima, Japan
Hiroyuki Ukida
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Pacific Northwest National Laboratory, Richland, USA
Pradeep Ramuhalli
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University of Applied Sciences Upper Austria, Wels, Austria
Kurt Niel
About the editors
Dr. Zheng Liu is an Associate Professor at the University of British Columbia, Kelowna, BC, Canada. Dr. Hiroyuki Ukida is an Associate Professor in the Institute of Technology and Science at the University of Tokushima, Japan. Dr. Pradeep Ramuhalli is a Senior Research Scientist at the Pacific Northwest National Laboratory, Richland, WA, USA. Dipl.-Ing. Kurt Niel is the Head of the Department of Metrology and Control Engineering at the University of Applied Sciences Upper Austria, Wels, Austria.
Bibliographic Information
Book Title: Integrated Imaging and Vision Techniques for Industrial Inspection
Book Subtitle: Advances and Applications
Editors: Zheng Liu, Hiroyuki Ukida, Pradeep Ramuhalli, Kurt Niel
Series Title: Advances in Computer Vision and Pattern Recognition
DOI: https://doi.org/10.1007/978-1-4471-6741-9
Publisher: Springer London
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag London (outside the USA) 2015
Hardcover ISBN: 978-1-4471-6740-2Published: 05 October 2015
Softcover ISBN: 978-1-4471-6980-2Published: 23 August 2016
eBook ISBN: 978-1-4471-6741-9Published: 24 September 2015
Series ISSN: 2191-6586
Series E-ISSN: 2191-6594
Edition Number: 1
Number of Pages: X, 541
Number of Illustrations: 394 b/w illustrations, 13 illustrations in colour
Topics: Image Processing and Computer Vision, Pattern Recognition