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Simulation in X-ray Testing

RL1, Publisher:, Link>


AUTHORS

Domingo Mery, Christian Pieringer


ABSTRACT

In order to evaluate the performance of computer vision techniques, computer simulation can be a useful tool. In this chapter, we review some basic concepts of the simulation of X-ray images, and present simple geometric and imaging models that can be used in the simulation. We explain the basic simulation principles and we address some techniques of simulated defects (that can be used to assess the performance of a computer vision method for automated defect recognition) and simulation of threat objects (that can be used to assess the performance of computer vision methods, to enhance the training dataset, or to improve a training program for human inspectors). Afterwards, the chapter gives an overview of the use of Generative Adversarial Networks (GANs) in the simulation of realistic X-ray images. Finally, we present ‘aRTist’, a simulation software that can be used to generate very realistic X-ray images. The chapter also has some Python examples that the reader can run and follow easily.

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