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BY-NC-ND 3.0 license Open Access Published by De Gruyter Open Access April 27, 2016

Tracking sub-atomic particles through the Attribute Space

  • M. Babai , N. Kalantar-Nayestanaki , J. G. Messchendorp and M. H. F. Wilkinson


In this paper, we present the results of an application of attribute space morphological filters for tracking sub-atomic particles in magnetic fields. For this purpose, we have applied the concept of attribute space and connectivity to the binary images produced by charged particles passing through the tracking detector for the future experiment PANDA. This detector could be considered as an undirected graph with irregular neighbourhood relations. For this project, we rely only on the detector geometry. In addition, we have extended the graph to estimate the z-coordinates of the particle paths. The result is an O(n2), proof of concept algorithm with a total error of approximately 0.17; this value depends on track multiplicity and particle type and its parameters. The results look promising; however, more work needs to be done to make this algorithm applicable for the real-life case.


[1] M. B. Kurdy and D. Jeulin. Directionalmathematical morphology operations. Proceedings of the Fifth European Congress for Stereology, 8/2:473 480, 1989. Search in Google Scholar

[2] Ben Appleton Hugues Talbot. Efficient complete and incomplete path openings and closings. Image and Vision Computing, 25(4):416 – 425, April 2007. 10.1016/j.imavis.2006.07.021Search in Google Scholar

[3] M. A. Westenberg, J. B. T. M. Roerdink, and M. H. F. Wilkinson. Volumetric attribute filtering and interactive visualization using the max-tree representation. IEEE Trans. Image Proc., 16:2943–2952, 2007. 10.1109/TIP.2007.909317Search in Google Scholar

[4] M. H. F. Wilkinson and M. A. Westenberg. Shape preserving filament enhancement filtering. In W. J. Niessen and M. A. Viergever, editors, Proc. MICCAI’2001, volume 2208 of Lecture Notes in Computer Science, pages 770–777, 2001. 10.1007/3-540-45468-3_92Search in Google Scholar

[5] Michael H.F. Wilkinson. Attribute-space connectivity and connected filters. Image and Vision Computing, 25(4):426 – 435, 2007. International Symposium on Mathematical Morphology 2005. 10.1016/j.imavis.2006.04.015Search in Google Scholar

[6] A. Toet H. J. A. M. Heijmans, P. Nacken and L. Vincent. Graph morphology. Journal of Visual Communication and Image Representation, 3:24 – 38, March 1992. 10.1016/1047-3203(92)90028-RSearch in Google Scholar

[7] Jean Cousty, Laurent Najman, Fabio Dias, and Jean Serra. Morphological filtering on graphs. Computer Vision and Image Understanding, 117(4):370 – 385, 2013. Special issue on Discrete Geometry for Computer Imagery. 10.1016/j.cviu.2012.08.016Search in Google Scholar

[8] (PANDA Collaboration) W. Erni, I. Keshelashvili, B. Krusche, et al. Technical design report for the panda straw tube tracker. The European Physical Journal A, 49:25, 2013. Special Article - Tools for Experiment and Theory. Search in Google Scholar

[9] C. Ronse. Set-theoretical algebraic approaches to connectivity in continuous or digital spaces. J. Math. Imag. Vis., 8:41 – 58, 1998. Search in Google Scholar

[10] J. Serra. Connectivity on complete lattices. J. Math. Imag. Vis., 9 (3):231 – 251, 1998. Search in Google Scholar

[11] E. J. Breen and R. Jones. Attribute openings, thinnings and granulometries. Comp. Vis. Image Understand., 64(3):377–389, 1996. 10.1006/cviu.1996.0066Search in Google Scholar

[12] M. H. F. Wilkinson and F. Schut. Digital image analysis of microbes: imaging, morphometry, fluorometry and motility techniques and applications. John Wiley & Sons Ltd., New York, NY, USA, 1st edition, 1998. Search in Google Scholar

Received: 2015-7-3
Accepted: 2016-2-11
Published Online: 2016-4-27

© 2016 M. Babai et al.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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