Motivated by the requirements of the present archaeology, we are developing an automated system for archaeological classification and reconstruction of ceramics. This paper shows different acquisition techniques in order to get 3D data of pottery and to compute the profile sections of fragments. With the enhancements shown in this paper, archaeologists get a tool to do archaeological documentation of pottery in an automated way.


Acquisition System Acquisition Device Range Accuracy Excavation Site Back View 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Beraldin, J.A., Atzeni, C., Guidi, G., Pieraccini, M., Lazzari, S.: Establishing a Digital 3d Imaging Laboratory for Heritage Applications: First Trials. In: Proceedings of the Italy-Canada 2001 Workshop on 3D Digital Imaging and Modeling Applications, Padova, on CD-ROM (2001)Google Scholar
  2. 2.
    Besl, P.J.: Active, optical range imaging sensors. Machine Vision and Applications 1(2), 127–152 (1988)CrossRefGoogle Scholar
  3. 3.
    Blais, F.: A Review of 20 Years of Range Sensor Development. In: SPIE Proceedings, Electronic Imaging, vol. 5013, pp. 62–76 (2003)Google Scholar
  4. 4.
    El-Hakim, S.F., Beraldin, J.A., Picard, M.: Detailed 3D Reconstruction of Monuments using multiple Techniques. In: Boehler, W. (ed.) Proceedings of ISPRS-CIPA Workshop on Scanning for Cultural Heritage Recording, Corfu, pp. 13–18 (2002)Google Scholar
  5. 5.
    Kampel, M.: 3D Mosaicing of Fractured Surfaces. PhD thesis, Vienna University of Technology (2003)Google Scholar
  6. 6.
    Kampel, M., Mara, H., Sablatnig, R.: Investigation on traditional and modern ceramic documentation. In: Vernazza, G., Sicuranza, G. (eds.) Proc. of ICIP 2005: Intl. Conf. on Image Processing, Genova, Italy, vol. 2, pp. 570–573 (September 2005)Google Scholar
  7. 7.
    Kampel, M., Sablatnig, R.: Color Classification of Archaeological Fragments. In: Sanfeliu, A., Villanueva, J.J., Vanrell, M., Alquezar, R., Jain, A.K., Kittler, J. (eds.) Proc. of 15th International Conference on Pattern Recognition, Barcelona, vol. 4, pp. 771–774. IEEE Computer Society Press, Los Alamitos (2000)CrossRefGoogle Scholar
  8. 8.
    Kampel, M., Sablatnig, R., Tosovic, S.: Volume based reconstruction of archaeological artifacts. In: Boehler, W. (ed.) Proc. of Intl. Workshop on Scanning for Cultural Heritage Recording, pp. 76–83 (2002)Google Scholar
  9. 9.
    Klette, R., Koschan, A., Schlüns, K.: Computer Vision - Räumliche Information aus digitalen Bildern. Vieweg (1996)Google Scholar
  10. 10.
    Orton, C., Tyers, P., Vince, A.: Pottery in archaeology. Cambridge University Press, Cambridge (1993)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Martin Kampel
    • 1
  1. 1.Vienna University of Technology,Image Processing and Pattern Rcognition GroupVienna

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