Computer Vision for X-Ray Testing
Imaging, Systems, Image Databases, and Algorithms
Authors: Mery, Domingo, Pieringer, Christian
- Presents a focus on the most important real-world applications of X-ray testing
- Updated edition featuring new material on deep learning, simulation approaches, and dual energy X-ray images
- Includes numerous examples in Python
- Provides supplementary material at an associated website, including slides, videos, and a database of X-ray images
Buy this book
- About this Textbook
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[FIRST EDITION] This accessible textbook presents an introduction to computer vision algorithms for industrially-relevant applications of X-ray testing. Features: introduces the mathematical background for monocular and multiple view geometry; describes the main techniques for image processing used in X-ray testing; presents a range of different representations for X-ray images, explaining how these enable new features to be extracted from the original image; examines a range of known X-ray image classifiers and classification strategies; discusses some basic concepts for the simulation of X-ray images and presents simple geometric and imaging models that can be used in the simulation; reviews a variety of applications for X-ray testing, from industrial inspection and baggage screening to the quality control of natural products; provides supporting material at an associated website, including a database of X-ray images and a Matlab toolbox for use with the book’s many examples.
- About the authors
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Dr. Domingo Mery is a Full Professor at the Machine Intelligence Group (GRIMA) of the Department of Computer Sciences, and Director of Research and Innovation at the School of Engineering, at the Pontifical Catholic University of Chile, Santiago, Chile. Dr. Christian Pieringer is an Adjunct Instructor at the same institution.
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Computer Vision for X-Ray Testing
- Book Subtitle
- Imaging, Systems, Image Databases, and Algorithms
- Authors
-
- Domingo Mery
- Christian Pieringer
- Copyright
- 2020
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer Nature Switzerland AG
- eBook ISBN
- 978-3-030-56769-9
- DOI
- 10.1007/978-3-030-56769-9
- Hardcover ISBN
- 978-3-030-56768-2
- Edition Number
- 2
- Number of Pages
- XXI, 447
- Number of Illustrations
- 60 b/w illustrations, 333 illustrations in colour
- Topics
*immediately available upon purchase as print book shipments may be delayed due to the COVID-19 crisis. ebook access is temporary and does not include ownership of the ebook. Only valid for books with an ebook version. Springer Reference Works and instructor copies are not included.
