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Statements

Subject Item
n2:RIV%2F00216305%3A26230%2F14%3APU112065%21RIV15-MSM-26230___
rdf:type
skos:Concept n14:Vysledek
dcterms:description
Bubble detection is a complicated tasks since varying lighting conditions changes considerably the appearance of bubbles in liquid. The two common techniques to detect circular objects such as bubbles, the geometry-based and appearance-based approaches, have their advantages and weaknesses. The geometry-based methods often fail to detect small blob-like bubbles that do not match the used geometrical model, and appearance-based approaches are vulnerable to appearance changes caused by, e.g., illumination. In this paper, we compare a geometry-based concentric circular arrangements (CCA) and appearance-based sliding window methods as well as their combinations in terms of bubble detection, gas volume computation, and size distribution estimation. The best bubble detection performance was achieved with the sliding window method whereas the most precise volume estimate was produced by the CCA method. The combination of the two approaches gave only a minor advantage compared to the base methods. Bubble detection is a complicated tasks since varying lighting conditions changes considerably the appearance of bubbles in liquid. The two common techniques to detect circular objects such as bubbles, the geometry-based and appearance-based approaches, have their advantages and weaknesses. The geometry-based methods often fail to detect small blob-like bubbles that do not match the used geometrical model, and appearance-based approaches are vulnerable to appearance changes caused by, e.g., illumination. In this paper, we compare a geometry-based concentric circular arrangements (CCA) and appearance-based sliding window methods as well as their combinations in terms of bubble detection, gas volume computation, and size distribution estimation. The best bubble detection performance was achieved with the sliding window method whereas the most precise volume estimate was produced by the CCA method. The combination of the two approaches gave only a minor advantage compared to the base methods.
dcterms:title
Comparison of Appearance-Based and Geometry-Based Bubble Detectors Comparison of Appearance-Based and Geometry-Based Bubble Detectors
skos:prefLabel
Comparison of Appearance-Based and Geometry-Based Bubble Detectors Comparison of Appearance-Based and Geometry-Based Bubble Detectors
skos:notation
RIV/00216305:26230/14:PU112065!RIV15-MSM-26230___
n3:aktivita
n4:P n4:S
n3:aktivity
P(ED1.1.00/02.0070), P(TE01020415), S
n3:dodaniDat
n5:2015
n3:domaciTvurceVysledku
n17:9340386 n17:7876645
n3:druhVysledku
n19:D
n3:duvernostUdaju
n15:S
n3:entitaPredkladatele
n11:predkladatel
n3:idSjednocenehoVysledku
8013
n3:idVysledku
RIV/00216305:26230/14:PU112065
n3:jazykVysledku
n20:eng
n3:klicovaSlova
Detection of Bubbles,
n3:klicoveSlovo
n16:Detection%20of%20Bubbles
n3:kontrolniKodProRIV
[ECDD6EB28F2A]
n3:mistoKonaniAkce
PJIIT - Polish-Japanese Institute of Information
n3:mistoVydani
Warsaw
n3:nazevZdroje
Proccedings of Internation Conference on Computer Vision and Graphics
n3:obor
n22:IN
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
6
n3:projekt
n10:TE01020415 n10:ED1.1.00%2F02.0070
n3:rokUplatneniVysledku
n5:2014
n3:tvurceVysledku
Lensu, Lasse Kälviäinen, Heikki Eerola, Tuomas Strokina, Nataliya Juránek, Roman Zemčík, Pavel
n3:typAkce
n18:EUR
n3:zahajeniAkce
2014-10-10+02:00
s:numberOfPages
8
n21:doi
10.1007/978-3-319-11331-9_73
n8:hasPublisher
Springer-Verlag
n7:isbn
978-3-319-11330-2
n12:organizacniJednotka
26230