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03944nam a22005295i 4500 |
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978-3-319-20747-6 |
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DE-He213 |
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20151204155943.0 |
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cr nn 008mamaa |
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150724s2015 gw | s |||| 0|eng d |
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|a 9783319207476
|9 978-3-319-20747-6
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|a 10.1007/978-3-319-20747-6
|2 doi
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|a Mery, Domingo.
|e author.
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|a Computer Vision for X-Ray Testing
|h [electronic resource] :
|b Imaging, Systems, Image Databases, and Algorithms /
|c by Domingo Mery.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2015.
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| 300 |
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|a XXIV, 347 p. 311 illus., 62 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a X-ray Testing -- Images for X-ray Testing -- Geometry in X-ray Testing -- X-ray Image Processing -- X-ray Image Representation -- Classification in X-ray Testing -- Simulation in X-ray Testing -- Applications in X-ray Testing -- Appendix A: GDXray Details -- Appendix B: XVIS Toolbox -- Quick Reference.
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|a This accessible textbook presents an introduction to computer vision algorithms for industrially-relevant applications of X-ray testing. Covering complex topics in an easy-to-understand way, without requiring any prior knowledge in the field, the book provides a concise review of the key methodologies in computer vision for solving important problems in industrial radiology. The theoretical coverage is supported by numerous examples, each of which can be tested and evaluated by the reader using a freely-available Matlab toolbox and X-ray image database. Topics and features: Introduces the mathematical background for monocular and multiple view geometry, which is commonly used in X-ray computer vision systems Describes the main techniques for image processing used in X-ray testing, including image filtering, edge detection, image segmentation and image restoration 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, and techniques for estimating the accuracy of a classifier 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 This classroom-tested and hands-on guide is ideal for graduate and advanced undergraduate students interested in the practical application of image processing, pattern recognition and computer vision techniques for non-destructive quality testing and security inspection.
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| 650 |
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|a Computer science.
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| 650 |
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|a Image processing.
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| 650 |
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|a Pattern recognition.
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| 650 |
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|a Quality control.
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| 650 |
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|a Reliability.
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|a Industrial safety.
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4 |
|a Computer Science.
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| 650 |
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4 |
|a Image Processing and Computer Vision.
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| 650 |
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|a Quality Control, Reliability, Safety and Risk.
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| 650 |
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4 |
|a Pattern Recognition.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer eBooks
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| 776 |
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8 |
|i Printed edition:
|z 9783319207469
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| 856 |
4 |
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|u http://dx.doi.org/10.1007/978-3-319-20747-6
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-SCS
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| 950 |
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|a Computer Science (Springer-11645)
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