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GDXray: The Database of X-ray Images for Nondestructive Testing

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Abstract

In this paper, we present a new dataset consisting of 19,407 X-ray images. The images are organized in a public database called \(\mathbb {GDX}\)ray that can be used free of charge, but for research and educational purposes only. 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 such cases, the coordinates of the bounding boxes of the objects of interest or the labels of the images are available in standard text files. The size of \(\mathbb {GDX}\)ray is 3.5 GB and it can be downloaded from our website. We believe that \(\mathbb {GDX}\)ray represents a relevant contribution to the X-ray testing community. On the one hand, students, researchers and engineers can use these X-ray images to develop, test and evaluate image analysis and computer vision algorithms without purchasing expensive X-ray equipment. On the other hand, these images can be used as a benchmark in order to test and compare the performance of different approaches on the same data. Moreover, the database can be used in the training programs of human inspectors.

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Notes

  1. See for example a good collection in http://www.via.cornell.edu/databases/.

  2. There are some galleries of X-ray images available on the web with a few samples, see for instance http://www.vidisco.com/ndt_solutions/ndt_info_center/ndt_x_ray_gallery with approximately 50 X-ray images.

  3. Grima, from Grupo de Inteligencia de Máquina, is the name of our Machine Intelligence Group at the Department of Computer Science of the Pontificia Universidad Católica de Chile http://grima.ing.puc.cl. The X-ray images included in \(\mathbb {GDX}\)ray can be used free of charge, for research and educational purposes only. Redistribution and commercial use is prohibited. Any researcher reporting results which use this database should acknowledge the \(\mathbb {GDX}\)ray database by citing this paper.

  4. See http://www.libpng.org/pub/png/.

  5. The X-ray images of series W0001 and W0003 are included in GDXray thanks to the collaboration of the BAM Federal Institute for Materials Research and Testing, Berlin, Germany http://dir.bam.de/dir.html.

  6. The original images in TIFF format are available also in series W0003 as files RRT01.zip (the first 31 images) and RRT02.zip (the last 36 images).

References

  1. Carrasco, M., Mery, D.: Segmentation of welding defects using a robust algorithm. Mater. Eval. 62(11), 1142–1147 (2004)

    Google Scholar 

  2. Carrasco, M., Mery, D.: Automatic multiple view inspection using geometrical tracking and feature analysis in aluminum wheels. Mach. Vis. Appl. 22(1), 157–170 (2011)

    Article  Google Scholar 

  3. Damashek, A., Doherty, J.: Detecting guns using parametric edge matching. Tech. Rep. Project for Computer Vision Course: CS231A, Stanford University (2015)

  4. Ghoreyshi, A., Vidal, R., Mery, D.: Segmentation of circular casting defects using a robust algorithm. Insight-Non-Destruct. Test. Cond. Monit. 47(10), 615–617 (2005)

    Article  Google Scholar 

  5. Hernández, S., Sáez, D., Mery, D., da Silva, R., Sequeira, M.: Automated defect detection in aluminium castings and welds using neuro-fuzzy classifiers. In: Proceedings of the 16th World Conference on Non-destructive Testing (WCNDT–2004), Montreal (2004)

  6. Huang, Q., Wu, Y., Baruch, J., Jiang, P., Peng, Y.: A template model for defect simulation for evaluating nondestructive testing in X-radiography. IEEE Trans. Syst. Man Cybern. A: Syst. Hum. 39(2), 466–475 (2009)

  7. Mery, D.: A new algorithm for flaw simulation in castings by superimposing projections of 3D models onto X-ray images. In: Proceedings of the XXI International Conference of the Chilean Computer Science Society (SCCC-2001), pp. 193–202. IEEE Computer Society Press, Punta Arenas (2001)

  8. Mery, D.: Crossing line profile: a new approach to detecting defects in aluminium castings. In: Proceedings of the Scandinavian Conference on Image Analysis (SCIA 2003), Lecture Notes in Computer Science, vol. 2749, pp. 725–732 (2003)

  9. Mery, D.: Explicit geometric model of a radioscopic imaging system. NDT & E Int. 36(8), 587–599 (2003)

    Article  Google Scholar 

  10. Mery, D.: Automated detection in complex objects using a tracking algorithm in multiple X-ray views. In: Proceedings of the 8th IEEE Workshop on Object Tracking and Classification Beyond the Visible Spectrum (OTCBVS 2011), in Conjunction with CVPR 2011, pp. 41–48. Colorado Springs (2011)

  11. Mery, D.: Automated detection of welding defects without segmentation. Mater. Eval. 69(6), 657–663 (2011)

    Google Scholar 

  12. Mery, D.: Inspection of complex objects using multiple-X-ray views. IEEE/ASME Trans. Mechatron. 20(1), 338–347 (2015)

    Article  MathSciNet  Google Scholar 

  13. Mery, D., Berti, M.A.: Automatic detection of welding defects using texture features. Insight-Non-Destruct. Test. Cond. Monit. 45(10), 676–681 (2003)

    Article  Google Scholar 

  14. Mery, D., Carrasco, M.: Automated multiple view inspection based on uncalibrated image sequences. Lect. Notes Comput. Sci. 3540, 1238–1247 (2005)

    Article  Google Scholar 

  15. Mery, D., Chacón, M., Munoz, L., González, L.: Automated inspection of aluminium castings using fusion strategies. Mater. Eval. 63(2), 148–153 (2005)

    Google Scholar 

  16. Mery, D., Filbert, D.: The epipolar geometry in the radioscopy: theory and application. Automatisierungstechnik 48(12), 588–596 (2000). (in German)

    Google Scholar 

  17. Mery, D., Filbert, D.: A fast non-iterative algorithm for the removal of blur caused by uniform linear motion in X-ray images. In: Proceedings of the 15th World Conference on Non-destructive Testing (WCNDT–2000), Rome (2000)

  18. Mery, D., Filbert, D.: Automated flaw detection in aluminum castings based on the tracking of potential defects in a radioscopic image sequence. IEEE Trans. Robot. Autom. 18(6), 890–901 (2002)

    Article  Google Scholar 

  19. Mery, D., Filbert, D.: Automated inspection of moving aluminium castings. In: 8th European Conference on Non-destructive Testing (ECNDT 2002), Barcelona (2002)

  20. Mery, D., Hahn, D., Hitschfeld, N.: Simulation of defects in aluminum castings using CAD models of flaws and real X-ray images. Insight 47(10), 618–624 (2005)

    Article  Google Scholar 

  21. Mery, D., Lillo, I., Riffo, V., Soto, A., Cipriano, A., Aguilera, J.: Automated fish bone detection using X-ray testing. J. Food Eng. 2011(105), 485–492 (2011)

    Article  Google Scholar 

  22. Mery, D., Pedreschi, F., Soto, A.: Automated design of a computer vision system for visual food quality evaluation. Food Bioprocess Technol. 6(8), 2093–2108 (2013)

    Article  Google Scholar 

  23. Mery, D., Riffo, V., Mondragon, G., Zuccar, I.: Detection of regular objects in baggages using multiple X-ray views. Insight 55(1), 16–21 (2013)

    Article  Google Scholar 

  24. Mery, D., Riffo, V., Zuccar, I., Pieringer, C.: Automated X-ray object recognition using an efficient search algorithm in multiple views. In: Proceedings of the 9th IEEE CVPR Workshop on Perception Beyond the Visible Spectrum, Portland (2013)

  25. Mondragón, G., Leiva, G., Aguilera, J., Mery, D.: Automated detection of softening and hard columella in kiwifruits during postharvest using X-ray testing. In: Proceedings of International Congress on Engineering and Food (2011)

  26. Perner, P., Zscherpel, U., Jacobsen, C.: A comparison between neural networks and decision trees based on data from industrial radiographic testing. Pattern Recogn. Lett. 22(1), 47–54 (2001)

    Article  MATH  Google Scholar 

  27. Pieringer, C., Mery, D.: Flaw detection in aluminium die castings using simultaneous combination of multiple views. Insight 52(10), 548–552 (2010)

  28. Pizarro, L., Mery, D., Delpiano, R., Carrasco, M.: Robust automated multiple view inspection. Pattern Anal. Appl. 11(1), 21–32 (2008)

    Article  MathSciNet  Google Scholar 

  29. Ramírez, F., Allende, H.: Detection of flaws in aluminium castings: a comparative study between generative and discriminant approaches. Insight-Non-Destruct. Test. Cond. Monit. 55(7), 366–371 (2013)

    Article  Google Scholar 

  30. Riffo, V., Mery, D.: Active X-ray testing of complex objects. Insight 54(1), 28–35 (2012)

    Article  Google Scholar 

  31. da Silva, R.R., Siqueira, M.H., de Souza, M.P.V., Rebello, J.M., Calôba, L.P.: Estimated accuracy of classification of defects detected in welded joints by radiographic tests. NDT & E Int. 38(5), 335–343 (2005)

    Article  Google Scholar 

Download references

Acknowledgments

Fondecyt Grant No. 1130934 from CONICYT–Chile.

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Authors and Affiliations

  1. Department of Computer Science, Pontificia Universidad Católica de Chile, Santiago, Chile

    Domingo Mery, Vladimir Riffo, German Mondragón, Iván Lillo & Hans Lobel

  2. Departamento de Ingeniería Informática y Ciencias de la Computación–Universidad de Atacama, Copiapó, Chile

    Vladimir Riffo

  3. BAM Federal Institute for Materials Research and Testing, Berlin, Germany

    Uwe Zscherpel

  4. Departamento de Ingeniería Informática–Universidad de Santiago de Chile, Santiago, Chile

    Irene Zuccar

  5. Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, Santiago, Chile

    Miguel Carrasco

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  1. Domingo Mery
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Correspondence to Domingo Mery.

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Mery, D., Riffo, V., Zscherpel, U. et al. GDXray: The Database of X-ray Images for Nondestructive Testing. J Nondestruct Eval 34, 42 (2015). https://doi.org/10.1007/s10921-015-0315-7

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