Computer Vision for X-Ray Testing: Imaging, Systems, Image by Domingo Mery

By Domingo Mery

This available textbook offers an creation to computing device imaginative and prescient algorithms for industrially-relevant purposes of X-ray checking out. gains: introduces the mathematical heritage for monocular and a number of view geometry; describes the most options for picture processing utilized in X-ray trying out; offers a variety of varied representations for X-ray photographs, explaining how those permit new good points to be extracted from the unique photo; examines a number of recognized X-ray photo classifiers and type ideas; discusses a few simple ideas for the simulation of X-ray photographs and offers basic geometric and imaging versions that may be utilized in the simulation; studies numerous purposes for X-ray trying out, from commercial inspection and luggage screening to the standard keep watch over of typical items; offers assisting fabric at an linked web site, together with a database of X-ray pictures and a Matlab toolbox to be used with the book’s many examples.

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The light strikes the photocathode and sets photoelectrons. These electrons are accelerated by approximately 25 kV, which are represented with reduced electron optics on an output phosphor screen. The output image of the image intensifier is then captured by a CCD camera. The disadvantage of the image intensifier is the geometric distortion due to the curvature of the input screen; details for this can be found in Sect. 2. Fig. 4 X-ray Testing System 15 Fig. 4 CCD Camera CCD cameras use solid-state imaging sensors based on CCD (charge-coupled device) arrays.

18(6), 890–901 (2002) References 33 59. : High precision X-ray stereo for automated 3D CAD-based inspection. IEEE Trans. Robot. Autom. 14(2), 292–302 (1998) 60. : Exploiting multiple view geometry in X-ray testing: part I, theory. Mater. Eval. 61(11), 1226–1233 (2003) 61. : Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004) Chapter 2 Images for X-ray Testing Abstract In this chapter, we present the dataset that is used in this book to illustrate and test several methods.

2 and Appendix A. The database includes five groups of X-ray images: castings, welds, baggage, natural objects, and settings. Each group has several series, and each series several X-ray images. Most of the series are annotated or labeled. In those cases, the coordinates of the bounding boxes of the objects of interest or the labels of the images are available in standard text files. 5 GB. php/material/gdxray/. 7 Summary In this book, we present a general overview of computer vision approaches that have been used in X-ray testing.

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