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Statements

Subject Item
n2:RIV%2F61989100%3A27600%2F10%3A86076541%21RIV11-MSM-27600___
rdf:type
skos:Concept n11:Vysledek
dcterms:description
This paper addresses the problem of automatic pattern classification in real metallographic images from the steel plant ArcelorMittal Ostrava plc (Ostrava, Czech Republic). Images of manufactured metal plates contain dark dots, i.e. imperfections. We monitor the process quality in the steel plant by determining automatically the number and sizes of these dots which represent plates' imperfections. The proposed algorithm segments the area of plates that contains dots, identifies rows of pixels that contain them, marks and counts them. The obtained results are promising and confirm that the proposed algorithm should serve as the foundation for future research in this area. This paper addresses the problem of automatic pattern classification in real metallographic images from the steel plant ArcelorMittal Ostrava plc (Ostrava, Czech Republic). Images of manufactured metal plates contain dark dots, i.e. imperfections. We monitor the process quality in the steel plant by determining automatically the number and sizes of these dots which represent plates' imperfections. The proposed algorithm segments the area of plates that contains dots, identifies rows of pixels that contain them, marks and counts them. The obtained results are promising and confirm that the proposed algorithm should serve as the foundation for future research in this area.
dcterms:title
Automatic Pattern Classification of Real Metallographic Images Automatic Pattern Classification of Real Metallographic Images
skos:prefLabel
Automatic Pattern Classification of Real Metallographic Images Automatic Pattern Classification of Real Metallographic Images
skos:notation
RIV/61989100:27600/10:86076541!RIV11-MSM-27600___
n3:aktivita
n17:P
n3:aktivity
P(1M06047)
n3:dodaniDat
n10:2011
n3:domaciTvurceVysledku
n14:3044521
n3:druhVysledku
n12:D
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n21:predkladatel
n3:idSjednocenehoVysledku
248193
n3:idVysledku
RIV/61989100:27600/10:86076541
n3:jazykVysledku
n9:eng
n3:klicovaSlova
automatic optical inspection, image classification, image resolution, image segmentation, metallography, quality management, steel industry
n3:klicoveSlovo
n4:automatic%20optical%20inspection n4:image%20classification n4:image%20segmentation n4:metallography n4:quality%20management n4:steel%20industry n4:image%20resolution
n3:kontrolniKodProRIV
[4D067BC6CFB0]
n3:mistoKonaniAkce
Houston, USA
n3:mistoVydani
NEW YORK
n3:nazevZdroje
2009 IEEE Industry Applications Society Annual Meeting
n3:obor
n8:BB
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
5
n3:projekt
n16:1M06047
n3:rokUplatneniVysledku
n10:2010
n3:tvurceVysledku
Válek, Ladislav Praks, Pavel Vincelette, Robert Tameze, Claude Zeljkovic, Vesna
n3:typAkce
n19:WRD
n3:wos
000275738800042
n3:zahajeniAkce
2009-10-04+02:00
s:issn
0197-2618
s:numberOfPages
4
n5:hasPublisher
IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
n13:isbn
978-1-4244-3475-6
n18:organizacniJednotka
27600