Abstract
A three dimensional (3-D) digital image emerges as a straightforward extension of a two dimensional (2-D) digital image. A 3-D digital image can be obtained by digitizing the 3-D space in which one or more objects of interest can be contained. From each object in the digital image, several features describing their geometry and topology can be computed. One of these features is the Euler number. An alternative method to compute the Euler number of a 3-D digital object (image) in terms of a codification of the vertices of the object voxels is described. The set of formal propositions baseline of the proposal operation are provided, demonstrated and numerically validated with simple objects. Examples with images of different complexity show the applicability of the proposal. The proposed method emerges as an extension of the proposal introduced for the 2-D case in [21] and as alternative of the formulation well described in [22].
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
(a voxel with the value 1).
References
Lin, X., Xiang, Sh., Gu, Y.: A new approach to compute the Euler number of 3D image. In: Proceedings of the 3rd IEEE Conference on Industrial Electronics and Applications, pp. 1543–1546. IEEE, Singapore (2008)
Lee, C.N., Poston, T., Rosenfeld, A.: Winding and Euler numbers for 2D and 3D digital images. CVGIP: Graph. Models Image Process. 53(6), 522–537 (1991)
Lee, C.N., Poston, T., Rosenfeld, A.: Holes and Genus of 2D and 3D digital images. CVGIP: Graph. Models Image Process. 55(1), 20–47 (1993)
Toriwaki, J., Yonekura, T.: Euler number and connectivity indexes of a three dimensional digital picture. Forma 17, 183–209 (2002)
Gray, S.B.: Local properties of binary images in two and three dimensions. IEEE Trans. Comput. C-20(5), 551–561 (1970)
Park, C.M., Rosenfeld, A.: Connectivity and genus in three dimension, TR-156. Computer Vision Laboratory, Computer Science Center, University of Maryland, College Park, MD (1971)
Kong, T.Y., Rosenfeld, A.: Digital topology: introduction and survey. Comput. Vis. Graph. Image Process. 48, 357–393 (1989)
Lee, C.N., Rosenfeld, A.: Computing the Euler number of a 3D image. In: Proceedings of the IEEE First International Conference on Computer Vision, pp. 567–571. IEEE (1987)
Xia, F.: BIUP3: boundary topological invariant of 3D objects through front propagation at a constant speed. In: Proceedings of the Geometric Modelling and Processing. IEEE (2004)
Bonnassie, A., Peyrin, F., Attaly, D.: Shape description of three-dimensional images based on medial axis. In: Proceedings of the 2001 International Conference on Image Processing, pp. 931–934. IEEE (2001)
Schladitz, K., Ohser, J., Nagel, W.: Measuring intrinsic volumes in digital 3D images. In: Kuba, A., Nyúl, L.G., Palágyi, K. (eds.) DGCI 2006. LNCS, vol. 4245, pp. 247–258. Springer, Heidelberg (2006). https://doi.org/10.1007/11907350_21
Saha, P.K., Chaudhuri, B.B.: A new approach to computing the Euler characteristic. Pattern Recogn. 28(12), 1955–1963 (1995)
Sánchez, H., Sossa, H., Braumann, U.-D., Bribiesca, E.: The Euler-Poincaré formula through contact surfaces of voxelized objects. J. Appl. Res. Technol. 11, 55–78 (2013)
Uchiyama, T., Taniazawa, T., Muramatsu, H., Endo, N., Takahashi, H.E., Hara, T.: Three-dimensional microstructural analysis of human trabecular bone in relation to its mechanical properties. Bone 25(4), 487–491 (1999)
Vogel, H.J., Roth, K.: Quantitative morphology and network representation of soil pore structure. Adv. Water Resour. 24, 233–242 (2001)
Lang, C., Ohser, J., Hilfer, R.: On the analysis of spatial binary images. J. Microsc. 203(3), 303–313 (2001)
Lehmann, P., et al.: Impact of geometrical properties on permeability and fluid phase distribution in porous media. Adv. Water Resour. 31, 1188–1204 (2008)
Velichko, A., Holzapfel, C., Siefers, A., Schladitz, K., Mücklich, F.: Unambiguous classification of complex microstructures by their three-dimensional parameters applied to graphite in cast iron. Acta Materialia 56, 1981–1990 (2008)
Ohser, J., Mücklich, F.: Statistical Analysis of Microstructures in Materials Science. Wiley, New York (2000)
Russ, J.C., Dehoff, R.: Practical Stereology. Kluwer Academic/Plenum, New York (2000)
Sossa, H., Santiago, R., Rubio, E., Pérez, M.: Computing the Euler number of a binary image based on a vertex codification. J. Appl. Res. Technol. 11, 360–370 (2013)
Sossa, H., Sánchez, H.: Computing the number of bubbles and tunnels of a 3-D binary object. In: Fred, A., De Marsico, M., Sanniti di Baja, G. (eds.) ICPRAM 2016. LNCS, vol. 10163, pp. 194–211. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-53375-9_11
Acknowledgements
The authors would like to thank the Instituto Politécnico Nacional for the support to carry out this research. H. Sossa appreciates the economic support received from the SIP-IPN and CONACYT under grants 20190007 and 65 (Frontiers of Science), respectively, to conduct this investigation.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Sossa, H., Rubío, E., Ponce, V., Sánchez, H. (2019). Vertex Codification Applied to 3-D Binary Image Euler Number Computation. In: Martínez-Villaseñor, L., Batyrshin, I., Marín-Hernández, A. (eds) Advances in Soft Computing. MICAI 2019. Lecture Notes in Computer Science(), vol 11835. Springer, Cham. https://doi.org/10.1007/978-3-030-33749-0_56
Download citation
DOI: https://doi.org/10.1007/978-3-030-33749-0_56
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-33748-3
Online ISBN: 978-3-030-33749-0
eBook Packages: Computer ScienceComputer Science (R0)