Comparison of methods for flow border detection in images of smoke visualization

dc.contributor.authorCaletka, Petrcs
dc.contributor.authorPech, Ondřejcs
dc.contributor.authorJedelský, Jancs
dc.contributor.authorLízal, Františekcs
dc.contributor.authorJícha, Miroslavcs
dc.coverage.volume114cs
dc.date.accessioned2017-09-22T10:47:16Z
dc.date.available2017-09-22T10:47:16Z
dc.date.issued2016-03-28cs
dc.description.abstractA separation of the flow region from the surroundings is an essential step in the analysis of smoke visualization images. The separation can be performed using several detection methods from the image segmentation group. This paper deals with the border detection of the air flow downstream of a benchmark automotive vent using different threshold-based detection methods. An assessment of the methods on the basis of the resulting image quality is also addressed. The quality level depends on the quantity and brightness of disturbances in the background area. The disturbance is usually an isolated region of smoke, which naturally cannot be a part of the flow. Three representative images of different quality levels were selected for the detection, and three methods were used for the evaluation. Each of the methods was used to determine the threshold differently (by the level, by the ratio, and by the change of brightness). It is demonstrated that the change-based method with an appropriately selected parameter is the most convenient for images with the worst quality level while level- and ratio-based methods are only applicable for images of good quality.en
dc.description.abstractA separation of the flow region from the surroundings is an essential step in the analysis of smoke visualization images. The separation can be performed using several detection methods from the image segmentation group. This paper deals with the border detection of the air flow downstream of a benchmark automotive vent using different threshold-based detection methods. An assessment of the methods on the basis of the resulting image quality is also addressed. The quality level depends on the quantity and brightness of disturbances in the background area. The disturbance is usually an isolated region of smoke, which naturally cannot be a part of the flow. Three representative images of different quality levels were selected for the detection, and three methods were used for the evaluation. Each of the methods was used to determine the threshold differently (by the level, by the ratio, and by the change of brightness). It is demonstrated that the change-based method with an appropriately selected parameter is the most convenient for images with the worst quality level while level- and ratio-based methods are only applicable for images of good quality.cs
dc.formattextcs
dc.format.extent1-4cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationEPJ Web of Conferences. 2016, vol. 114, p. 1-4.en
dc.identifier.doi10.1051/epjconf/201611402009cs
dc.identifier.issn2100-014Xcs
dc.identifier.other119741cs
dc.identifier.urihttp://hdl.handle.net/11012/70019
dc.language.isoencs
dc.publisherEDP Sciencescs
dc.relation.ispartofEPJ Web of Conferencescs
dc.relation.urihttp://www.epj-conferences.org/articles/epjconf/abs/2016/09/epjconf_efm2016_02009/epjconf_efm2016_02009.htmlcs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/2100-014X/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectCar venten
dc.subjectsmoke visualizationen
dc.subjectborder detectionen
dc.subjectCar vent
dc.subjectsmoke vizualization
dc.subjectborder detection
dc.titleComparison of methods for flow border detection in images of smoke visualizationen
dc.title.alternativeComparison of methods for flow border detection in images of smoke visualizationcs
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-119741en
sync.item.dbtypeVAVen
sync.item.insts2020.03.31 00:58:57en
sync.item.modts2020.03.30 22:54:00en
thesis.grantorVysoké učení technické v Brně. Fakulta strojního inženýrství. Energetický ústavcs
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
epjconf_efm2016_02009.pdf
Size:
842.16 KB
Format:
Adobe Portable Document Format
Description:
epjconf_efm2016_02009.pdf