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Integrated Imaging and Vision Techniques for Industrial Inspection

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Cover of 'Integrated Imaging and Vision Techniques for Industrial Inspection'

Table of Contents

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    Book Overview
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    Chapter 1 Industrial Inspection with Open Eyes: Advance with Machine Vision Technology
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    Chapter 2 Infrared Vision: Visual Inspection Beyond the Visible Spectrum
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    Chapter 3 Inspection Methods for Metal Surfaces: Image Acquisition and Algorithms for the Characterization of Defects
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    Chapter 4 FlexWarp, a Fast and Flexible Method for High-Precision Image Registration: A Nonparametric Approach for Precise Image Registration Applied to Industrial Print Inspection
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    Chapter 5 How Optical CMMs and 3D Scanning Will Revolutionize the 3D Metrology World
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    Chapter 6 Fast Three-Dimensional Shape Inspection Using a Multi-sided Mirror
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    Chapter 7 Efficient Completeness Inspection Using Real-Time 3D Color Reconstruction with a Dual-Laser Triangulation System
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    Chapter 8 X-ray Computed Tomography for Non-destructive Testing and Materials Characterization
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    Chapter 9 Defect Inspection for Curved Surface with Highly Specular Reflection
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    Chapter 10 Robotic Inspection Systems
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    Chapter 11 Machine Vision Techniques for Condition Assessment of Civil Infrastructure
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    Chapter 12 Smart Check 3D: An Industrial Inspection System Combining 3D Vision with Automatic Planning of Inspection Viewpoints
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    Chapter 13 Ultrasonic Evaluation and Imaging
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    Chapter 14 Nondestructive Visualization Using Electromagnetic Waves for Real and Practical Sensing Technology for Robotics
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    Chapter 15 Principles of Magneto-optic Imaging and Its Applications
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1 patent
1 Wikipedia page


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Integrated Imaging and Vision Techniques for Industrial Inspection
Published by
Springer-Verlag London, January 2015
DOI 10.1007/978-1-4471-6741-9
978-1-4471-6740-2, 978-1-4471-6741-9

Zheng Liu, Hiroyuki Ukida, Pradeep Ramuhalli, Kurt Niel

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 1%
Unknown 78 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 25%
Student > Master 17 22%
Student > Bachelor 11 14%
Researcher 6 8%
Student > Doctoral Student 5 6%
Other 8 10%
Unknown 12 15%
Readers by discipline Count As %
Engineering 44 56%
Computer Science 6 8%
Agricultural and Biological Sciences 3 4%
Economics, Econometrics and Finance 2 3%
Energy 2 3%
Other 9 11%
Unknown 13 16%