Computer Vision for X-Ray Testing: Imaging, Systems, Image Databases, and Algorithms [Hardcover]

[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 books many examples.

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.

Building on its strengths as a uniquely accessible textbook combining computer vision and X-ray testing, this enhanced second edition now firmly addresses core developments in deep learning and vision, providing numerous examples and functions using the Python language.  

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 probllp