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Selection in a 3D microtomographic image the region with the highest quality

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dc.contributor.authorSafonov, I. V.
dc.contributor.authorYakimchuk, I. V.
dc.contributor.authorKornilov, A. S.
dc.contributor.authorGoncharova, A. V.
dc.contributor.authorКорнилов, Антон Сергеевич
dc.date.accessioned2024-11-21T10:52:19Z
dc.date.available2024-11-21T10:52:19Z
dc.date.issued2019
dc.description.abstract© 2019 CEUR-WS. All rights reserved.We present an algorithm for processing of X-ray microtomographic (micro-CT) images that allows automatic selection of a sub-volume having the best visual quality for further mathematical simulation, for example, flow simulation. Frequently, an investigated sample occupies only a part of a volumetric image or the sample can be into a holder; a part of the image can be cropped. For each 2D slice across the Z-axis of an image, the proposed method locates a region corresponding to the sample. We explored applications of several existing blind quality measures for an estimation of the visual quality of a micro-CT image slice. Some of these metrics can be applied to ranking the image regions according to their quality. Our method searches for a cubic area located inside regions belonging to the sample and providing the maximal sum of the quality measures of slices crossing the cube across the Z-axis. The proposed technique was tested on synthetic and real micro-CT images of rocks.
dc.format.extentС. 160-168
dc.identifier.citationSelection in a 3D microtomographic image the region with the highest quality / Safonov, I.V. [et al.] // CEUR Workshop Proceedings. - 2019. - 2391. - P. 160-168
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85069658813&origin=resultslist
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/18509
dc.relation.ispartofCEUR Workshop Proceedings
dc.titleSelection in a 3D microtomographic image the region with the highest quality
dc.typeConference Paper
dspace.entity.typePublication
oaire.citation.volume2391
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relation.isAuthorOfPublication.latestForDiscovery1a1847b0-e43f-4541-9650-52e61b2bc844
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