Abstract
In this paper we propose a method for characterizing the surface of fractured pieces which come from old and complete original objects. Natural fractured pieces are difficult to segment due to the fact that the faces and edges are not well defined. For this reason, standard local feature based approaches are clearly inefficient to make an efficient segmentation. Our segmentation procedure is based on the Cone Curvature (CC) concept applied over the original dense models which provide standard scanner modeling tools. This CC based-method allows us to explore the surface from multiple neighborhood levels and to find a compact segmentation solution which characterizes different parts of the piece. A wide experimentation has been carried out on a set of old fractured pieces belonging to the remains of roman sculptures.
Chapter PDF
Similar content being viewed by others
References
Haralick, R.M., Shapiro, L.G.: Image Segmentation Techniques. Computer Vision, Graphics, and Image Processing (January 1985)
Pal, N.R., Pal, S.K.: A Review on Image Segmentation Techniques. Pattern Recognition (1993)
Liu, H.K.: Two and Three Dimensional Boundary Detection. Computer Graphics and Image Processing (April 1977)
Herman, G.T., Liu, H.K.: Dynamic Boundary Surface Detection. Computer Graphics and Image Processing (1978)
Zucker, S.W., Hummel, R.A.: An Optimal Three- dimensional Edge Operator. Technical report, McGil University, Toronto, Ontario, Canada (April 1979)
Huang, Q.-X.: Reassembling Fractured Objects by Geometric Matching. ACM Transactions on Graphics (TOG) archive 25(3) (July 2006)
Pottman, H., Wallner, J., Huang, Q.-X., Yang, Y.: Integral invariants for robust geometry processing. Computer Aided Geometric Design 26, 37–60 (2009)
Bellon, O., Silva, L.: New improvements to range image segmentation by edge detection. IEEE Signal Processing Letters 9(2), 43–45 (2002)
Gotardo, P., Bellon, O., Boyer, K., Silva, L.: Range Image Segmentation Into Planar and Quadric Surfaces Using an Improved Robust Estimator and Genetic Algorithm. IEEE Transactions on Systems, Man and Cybernetics. Part B, Cybernetics 34(6), 2303–2316 (2004)
Papaioannou, G., Karabassi, E.-A., Theoharis, T.: Virtual Archaeologist, Assembling the Past. IEEE, Computer Graphics and Applications 21, 53–59 (2001)
Papaioannou, G., Karabassi, E.-A., Theoharis, T.: Reconstruction of three-dimensional objects through matching of their parts. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(1), 114–124 (2002)
Papaioannou, G., Karabassi, E.-A.: Automatic Reconstruction of Archaeological Finds – A Graphics Approach. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(1), 114–124 (2002)
Adán, A., Adán, M.: A Flexible Similarity Measure for 3D Shapes Recognition. IEEE Transactions on Pattern Analysis and Machine Inteligence 26(11) (November 2004)
Adán, A., Adán, M., Salamanca, S., Merchán, P.: Using Non Local Features For 3D Shape Grouping. In: da Vitoria Lobo, N., Kasparis, T., Roli, F., Kwok, J.T., Georgiopoulos, M., Anagnostopoulos, G.C., Loog, M. (eds.) SSSPR 2008. LNCS, vol. 5342, pp. 644–653. Springer, Heidelberg (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Llanes, J., Adan, A., Salamanca, S. (2009). A New Segmentation Approach for Old Fractured Pieces. In: Bayro-Corrochano, E., Eklundh, JO. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2009. Lecture Notes in Computer Science, vol 5856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10268-4_19
Download citation
DOI: https://doi.org/10.1007/978-3-642-10268-4_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10267-7
Online ISBN: 978-3-642-10268-4
eBook Packages: Computer ScienceComputer Science (R0)