Abstract
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.
| Original language | English |
|---|---|
| Publisher | Springer International Publishing |
| Number of pages | 456 |
| ISBN (Electronic) | 9783030567699 |
| ISBN (Print) | 9783030567682 |
| DOIs | |
| State | Published - 21 Dec 2020 |
| Externally published | Yes |
Keywords
- Algorithms
- Computer Vision
- Deep Learning
- Dual Energy
- Image Analysis
- Image Processing
- Non-Destructive Testing
- Pattern Recognition
- Python
- Quality control, reliability, safety and risk
- Simulation
- X-Ray Testing