Abstract
The skeleton of an object is defined as the set of quench points formed during Blum’s grassfire transformation. Due to high sensitivity of quench points with small changes in the object boundary and the membership function (for fuzzy objects), often, a large number of redundant quench points is formed. Many of these quench points are caused by peripheral protrusions and dents and do not associate themselves with core shape features of the object. Here, we present a significance measure of quench points using the collision impact of fire-fronts and explore its role in filtering noisy quench points. The performance of the method is examined on three-dimensional shapes at different levels of noise and fuzziness, and compared with previous methods. The results have demonstrated that collision impact together with appropriate filtering kernels eliminate most of the noisy quench voxels while preserving those associated with core shape features of the object
Chapter PDF
Similar content being viewed by others
Keywords
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.
References
Saha, P.K., Strand, R., Borgefors, G.: Digital topology and geometry in medical imaging: a survey. IEEE Trans. Med. Imag. (in press)
Saha, P.K., Borgefors, G., Sanniti di Baja, G.: A survey on skeletonization algorithms and their applications. Pat. Reog. Lett. (in press)
Siddiqi, K., Pizer, S.M.: Medial representations: mathematics, algorithms and applications. Springer (2008)
Blum, H.: A transformation for extracting new descriptors of shape. Model. Percep. Speech Vis. Form 19, 362–380 (1967)
Arcelli, C., Sanniti di Baja, G.: Finding Local Maxima in a Pseudo-Euclidean Distance Transform. Comp. Vis. Grap. Im. Proc. 43, 361–367 (1988)
Borgefors, G., Ragnemalm, I., di Baja, G.S.: The Euclidean distance transform: finding the local maxima and reconstructing the shape. In: Proc 7th Scand. Conf. Imag. Anal., vol. 2, 974−981 (1991)
Borgefors, G.: Centres of maximal discs in the 5-7-11 distance transform. In: 8th Scandinavian Conference on Image Analysis, Tromsø, Norway, pp. 105−111 (1993)
Borgefors, G.: Distance transform in arbitrary dimensions. Comp. Vis. Grap. Im. Proc. 27, 321–345 (1984)
Borgefors, G.: Distance transformations in digital images. Comp. Vis. Grap. Im. Proc. 34, 344–371 (1986)
Saha, P.K., Wehrli, F.W.: Fuzzy distance transform in general digital grids and its applications. In: 7th Joint Conference on Information Sciences, pp. 201−213. Research Triangular Park, NC (2003)
Svensson, S.: Aspects on the reverse fuzzy distance transform. Patt. Recog. Lett. 29, 888–896 (2008)
Saha, P.K., Wehrli, F.W., Gomberg, B.R.: Fuzzy distance transform: theory, algorithms, and applications. Comp. Vis. Imag. Und. 86, 171–190 (2002)
Saha, P.K., Chaudhuri, B.B., Majumder, D.D.: A new shape preserving parallel thinning algorithm for 3D digital images. Pat. Recog. 30, 1939–1955 (1997)
Borgefors, G., Nyström, I.: Efficient shape representation by minimizing the set of centres of maximal discs/spheres. Pat. Recog. Lett. 18, 465–471 (1997)
Németh, G., Kardos, P., Palágyi, K.: Thinning combined with iteration-by-iteration smoothing for 3D binary images. Graph. Mod. 73, 335–345 (2011)
Arcelli, C., Sanniti di Baja, G., Serino, L.: Distance-driven skeletonization in voxel images. IEEE Trans. Patt. Anal. Mach. Intell. 33, 709–720 (2011)
Gagvani, N., Silver, D.: Parameter-controlled volume thinning. Graph. Mod. Imag. Proce. 61, 149–164 (1999)
Shah, J.: Gray skeletons and segmentation of shapes. Comp. Vis. Imag. Und. 99, 96–109 (2005)
Shah, J.: Skeletons of 3D shapes. In: Kimmel, R., Sochen, N.A., Weickert, J. (eds.) Scale-Space 2005. LNCS, vol. 3459, pp. 339–350. Springer, Heidelberg (2005)
Siddiqi, K., Bouix, S., Tannenbaum, A., Zucker, S.W.: Hamilton-Jacobi Skeletons. International Journal of Computer Vision 48, 215–231 (2002)
Jin, D., Saha, P.K.: A new fuzzy skeletonization algorithm and its applications to medical imaging. In: Petrosino, A. (ed.) ICIAP 2013, Part I. LNCS, vol. 8156, pp. 662–671. Springer, Heidelberg (2013)
Saha, P.K., Chaudhuri, B.B.: Detection of 3-D simple points for topology preserving transformations with application to thinning. IEEE Trans. Patt. Anal. Mach. Intell. 16, 1028–1032 (1994)
Saha, P.K., Chaudhuri, B.B.: 3D digital topology under binary transformation with applications. Comp. Vis. Image. Und. 63, 418–429 (1996)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Jin, D., Chen, C., Saha, P.K. (2015). Filtering Non-Significant Quench Points Using Collision Impact in Grassfire Propagation. In: Murino, V., Puppo, E. (eds) Image Analysis and Processing — ICIAP 2015. ICIAP 2015. Lecture Notes in Computer Science(), vol 9279. Springer, Cham. https://doi.org/10.1007/978-3-319-23231-7_39
Download citation
DOI: https://doi.org/10.1007/978-3-319-23231-7_39
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-23230-0
Online ISBN: 978-3-319-23231-7
eBook Packages: Computer ScienceComputer Science (R0)