Abstract
Automated X-ray Inspection (AXI) is useful for two types of application: detecting foreign bodies, particularly in food, and examining the internal detail of safety-critical products. At first sight, AXI merely seems to be a straightforward extension to Machine Vision but there are several complications. There is only a limited scope for adjusting the spectrum of an x-ray beam. It is not easy to build x-ray mirrors and lenses, so we cannot effectively focus, or collimate, an x-ray beam. Since an x-ray ray tube generates a conical beam, the images it forms are complicated. The diverging beam introduces parallax errors. Furthermore, objects near the x-ray source appear to be bigger than those further away. Features along the beam are superimposed, creating a jumble of detail that is difficult to analyse. AXI has its own set of special features that distinguishes it from other areas of Machine Vision. One particular point emphasises this. X-rays present a clear danger to health, so there is a need for good radiation screening and a variety of other safety measures. Mathematical and software modelling of AXI systems can often help in devising effective image analysis algorithms. These are simple and effective when inspecting close-tolerance accurately aligned artifacts. In this case, a point-by-point comparison of the test image and a reference image may be effective. As the image variability increases, more complex inspection algorithms may be required, often involving the use of sophisticated AI methods. The chapter concludes with a discussion of twin-beam x-ray systems that can improve the detection of defects and foreign bodies.
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Acknowledgements
Much of the material in this chapter was supplied by Dr. Mark Gravess, previously of Spectral Fusion Technologies, Birmingham, B46 1JT, UK, and was included in our joint book [13].
Much of the work on Twin Orthogonal Fan-beam (TOF) x-ray inspection systems was conducted by Stephen C. Palmer, working with the author on the project entitled “Automated 3D X-ray Inspection System for On-line Foreign Body Detection in Food Products”. This was funded under the Agro Industries Research (AIR) programme of the Commission of the European Communities – Directorate General XII. Reference number AIR2-CT93-1054.
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Batchelor, B.G. (2012). X-Ray Inspection. In: Batchelor, B.G. (eds) Machine Vision Handbook. Springer, London. https://doi.org/10.1007/978-1-84996-169-1_12
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