Machine Vision and Applications

, Volume 21, Issue 4, pp 413–425 | Cite as

Gamma/X-ray linear pushbroom stereo for 3D cargo inspection

  • Zhigang ZhuEmail author
  • Yu-Chi Hu
  • Li Zhao
Original Paper


For evaluating the contents of trucks, containers, cargo, and passenger vehicles by a non-intrusive gamma-ray or X-ray imaging system to determine the possible presence of contraband, three-dimensional (3D) measurements could provide more information than just 2D measurements. In this paper, a linear pushbroom scanning model is built for such a commonly used gamma-ray or X-ray cargo inspection system. Three-dimensional (3D) measurements of the objects inside a cargo can be obtained by effectively constructing a pushbroom stereo system using two such scanning systems with different scanning angles. A simple but robust calibration method is proposed to find the important parameters of the linear pushbroom sensors. Then, a fast stereo matching algorithm is developed to obtain 3D measurements of the objects under inspection. This algorithm is fully automatic based on free-form deformable registration. An interactive user interface is designed for 3D visualization of the objects of interest. Using the interactive tool, the automatic algorithm is also compared with a very simple semi-automatic algorithm based on point correlation. Experimental results of sensor calibration, stereo matching, 3D measurements and visualization of a 3D cargo container, and the objects inside, are presented.


Pushbroom imaging Automatic 3D measurements Stereo matching Cargo inspection Homeland security 


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  1. 1.
    Chai, J., Shum, H.-Y.: Parallel projections for stereo reconstruction. In: Proceedings of CVPR’00: II, pp. 493–500 (2000)Google Scholar
  2. 2.
    Dickson, P., Li, J., Zhu, Z., Hanson, A., Riseman, E., Sabrin, H., Schultz, H., Whitten, G.: Mosaic generation for under-vehicle inspection. IEEE Workshop on Applications of Computer Vision, Orlando, Florida, 3–4 December (2002)Google Scholar
  3. 3.
    Gupta R., Hartley R.: Linear pushbroom cameras. IEEE Trans. PAMI 19(9), 963–975 (1997)Google Scholar
  4. 4.
    Gupta, R., Noble, A., Hartley, R., Mundy, J., Schmitz, A.: Camera calibration for 2.5-D X-ray metrology. In: Proceedings of ICIP’95, vol. 3, October 23–26, Washington D.C. (1995)Google Scholar
  5. 5.
    Hardin, W.: Cargo inspection: imaging solutions wait for government’s call. Machine Vision Online, December (2002)Google Scholar
  6. 6.
    Hardin, W.: US Seaports: Finding the needle in hundreds of haystacks. Machine Vision Online, June (2004)Google Scholar
  7. 7.
    Hitachi: Cargo container X-ray inspection systems, Hitachi Rev. 53(2), 97–102 (2004).
  8. 8.
    Huang, F., Wei, S.K., Klette, R.: Rotating line cameras: epipolar geometry and spatial sampling (2006)
  9. 9.
    Keener J.P.: Principles of Applied Mathematics: Transformation and Approximation. Addison-Wesley, Reading (1998)Google Scholar
  10. 10.
    Klette, R., Gimel’farb, G., Reulke, R.: Wide-angle image acquisition, analysis and visualization. In: Proceedings of 14th International Conference on Vision Interface (VI’2001), Ottawa, Canada, June, pp. 114–125 (2001)Google Scholar
  11. 11.
    Koschan, D Page D., Ng, J.-C., Abidi, M., Gorsich, D., Gerhart, G.: SAFER under vehicle inspection through video mosaic building. Int. J. Ind. Robot 31(5), 435–442 (2004)CrossRefGoogle Scholar
  12. 12.
    Lu W., Chen M.L., Olivera G.H., Ruchala K.J., Mackie T.R.: Fast free-form deformable registration via calculus of variations. Phys. Med. Biol. 49, 3067–3087 (2004)CrossRefGoogle Scholar
  13. 13.
    Noble, A., Hartley, R., Mundy, J., Farley, J.: X-Ray metrology for quality assurance. In: Proceedings of IEEE ICRA’94, vol. 2, pp. 1113–1119 (1995)Google Scholar
  14. 14.
    Peleg S., Ben-Ezra M., Pritch Y.: Omnistereo: panoramic stereo imaging. IEEE Trans. PAMI 23(3), 279–290 (2001)Google Scholar
  15. 15.
    Shum, H.-Y., Szeliski, R.: Stereo reconstruction from multiperspective panoramas. In: Proceedings of ICCV’99, pp. 14–21 (1999)Google Scholar
  16. 16.
    Orphan, V.J., Richardson, R., Bowlin, D.W.: VACIS™—a safe, reliable and cost- effective cargo inspection technology, Port Technology International, pp. 61–65 (2002)
  17. 17.
    Xu, C.: Deformable models with application to human cerebral cortex reconstruction in magnetic resonance images. PhD Thesis, John Hopkins University (2000)Google Scholar
  18. 18.
    Zheng J.Y., Tsuji S.: Panoramic representation for route recognition by a mobile robot. Int. J. Comput. Vis. 9(1), 55–76 (1992)CrossRefGoogle Scholar
  19. 19.
    Zhu Z., Hanson A.R.: LAMP: 3D layered, adaptive-resolution and multi-perspective panorama—a new scene representation. Comput. Vis. Image Underst. 96(3), 294–326 (2004)CrossRefGoogle Scholar
  20. 20.
    Zhu, Z., Riseman, E.M., Hanson, A.R.: Parallel-perspective stereo mosaics. In: Proceedings of ICCV’01, vol. I, pp. 345–352 (2001)Google Scholar
  21. 21.
    Zhu Z., Riseman E.M., Hanson A.R.: Generalized parallel-perspective stereo mosaics from airborne videos. IEEE Trans. PAMI 26(2), 226–237 (2004)Google Scholar
  22. 22.
    Zhu, Z., Zhao, L., Lei, J.: 3D Measurements in cargo inspection with a gamma-ray linear pushbroom stereo system. In: IEEE Workshop on Advanced 3D Imaging for Safety and Security, June 25, San Diego, CA, USA (2005)
  23. 23.
    Zhu, Z., Hu, Y.-C.: Stereo Matching and 3D Visualization for Gamma-Ray Cargo Inspection. In: Proceedings of the Eighth IEEE Workshop on Applications of Computer Vision, 21–22 February , Austin, Texas, USA (2007)Google Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  1. 1.Department of Computer ScienceThe City College of New York/CUNYNew YorkUSA
  2. 2.PhD Program in Computer ScienceThe CUNY Graduate CenterNew YorkUSA
  3. 3.Department of Medical PhysicsMemorial Sloan-Kettering Cancer CenterNew YorkUSA
  4. 4.PhD Program in EconomicsThe CUNY Graduate CenterNew YorkUSA

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