Abstract
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 presence 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.
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Acknowledgements
This paper presents the results achieved in the framework of the Project no. 114-451-2723/2016-03 funded by the Provincial Secretariat for Higher Education and Scientific Research, and within the project TR - 35020, funded by the Ministry of Education, Science and Technological Development of Republic of Serbia. Project IKARUS supported parts of presented research (European Regional Development Fund, MIS: RC.2.2.08-0042, Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb).
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Sokac, M., Santosi, Z., Vukelic, D., Katic, M., Durakbasa, M.N., Budak, I. (2020). Enhancement of Images from Industrial X-Ray Computed Tomography Systems by Hybrid Approach. In: Durakbasa, N., Gençyılmaz, M. (eds) Proceedings of the International Symposium for Production Research 2019. ISPR ISPR 2019 2019. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-31343-2_12
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