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Buchbeiträge:

M. Sokac, Z. Santosi, D. Vukelic, M. Katic, M.N. Durakbasa, I. Budak:
"Enhancement of Images from Industrial X-Ray Computed Tomography Systems by Hybrid Approach";
in: "Proceedings of the International Symposium for Production Research 2019, Lecture Notes in Mechanical Engineering book series (LNME)", 1; M.N. Durakbasa, G. Gencyilmaz (Hrg.); Springer Nature Switzerland AG, Cham, Switzerland, 2019, ISBN: 978-3-030-31343-2, S. 138 - 146.



Kurzfassung englisch:
Application of the computed tomography (CT) within industry has been rising in recent years due to its non-destructive abilities and accuracy. Nevertheless, there are some challenges related to CT scanning, such as pres- ence of artefacts. The aim of this research is to investigate to what extent the application of some advanced algorithms can influence the accuracy of the X-ray CT images. In this paper, after a brief overview of different existing methods used for reduction of different types of artefacts, preliminary research of a new approach for CT image enhancement is presented. It is based on a hybrid methodology using two different methods - Fuzzy Clustering and Region Growing - joined in order to exploit their advantages. Results show that the proposed methodology contributes to CT image enhancement, with borders of segmented objects on CT images more easily extracted.

Schlagworte:
Computed tomography, X-ray CT, Artefacts, Industrial CT Images, Image processing


"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)
http://dx.doi.org/10.1007/978-3-030-31343-2_45


Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.