Abstract

X-ray testing has been developed for the inspection of materials or objects, where the aim is to analyse - non-destructively - those inner parts that are undetectable to the naked eye. Thus, X-ray testing is used to determine whether a test object deviates from a given set of specifications. Typical applications are the inspection of automotive parts, quality control of welds, screening of baggage, analysis of food products and inspection of cargo. In order to achieve efficient and effective X-ray testing, automated and semi-automated systems based on computer vision algorithms are being developed to execute this task. In this paper, we present a general overview of the computer vision approaches that have been used in X-ray testing. In addition, we review some techniques that have been applied in certain relevant applications and introduce a public database of X-ray images that can be used for testing and evaluation of image analysis and computer vision algorithms. Finally, we conclude that there are some areas, such as casting inspection, where automated systems are very effective and other application areas, such as baggage screening, where human inspection is still used. There are certain application areas, such as weld and cargo inspection, where the process is semi-automatic and there is some research in areas, including food analysis, where processes are beginning to be characterised by the use of X-ray imaging.