Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/14307
Title: Enhancement of Images from Industrial X-Ray Computed Tomography Systems by Hybrid Approach
Authors: Šokac, Mario 
Santoši, Željko 
Vukelić, Đorđe 
Katic M.
Durakbasa M.
Budak, Igor 
Issue Date: 1-Jan-2020
Journal: Lecture Notes in Mechanical Engineering
Abstract: © 2020, Springer Nature Switzerland AG. 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.
URI: https://open.uns.ac.rs/handle/123456789/14307
ISBN: 9783030313425
ISSN: 21954356
DOI: 10.1007/978-3-030-31343-2_12
Appears in Collections:FTN Publikacije/Publications

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