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Statements

Subject Item
n2:RIV%2F61989100%3A27740%2F12%3A86084961%21RIV13-MPO-27740___
rdf:type
n12:Vysledek skos:Concept
dcterms:description
The aim of the research is development and testing of new methods to classify the quality of metallographic samples of steels with high added value (for example grades X70 according API). In this paper, we address the development of methods to classify the quality of slab samples images with the main emphasis on the quality of the image center called as segregation area. For this reason, we introduce an alternative method for automated retrieval of region of interest. In the first step, the metallographic image is segmented using both spectral method and thresholding. Then, the extracted macrostructure of the metallographic image is automatically analyzed by statistical methods. Finally, automatically extracted region of interests are compared with results of human experts. Practical experience with retrieval of non-homogeneous noised digital images in industrial environment is discussed as well. The aim of the research is development and testing of new methods to classify the quality of metallographic samples of steels with high added value (for example grades X70 according API). In this paper, we address the development of methods to classify the quality of slab samples images with the main emphasis on the quality of the image center called as segregation area. For this reason, we introduce an alternative method for automated retrieval of region of interest. In the first step, the metallographic image is segmented using both spectral method and thresholding. Then, the extracted macrostructure of the metallographic image is automatically analyzed by statistical methods. Finally, automatically extracted region of interests are compared with results of human experts. Practical experience with retrieval of non-homogeneous noised digital images in industrial environment is discussed as well.
dcterms:title
Automated region of interest retrieval of metallographic images for quality classification in industry Automated region of interest retrieval of metallographic images for quality classification in industry
skos:prefLabel
Automated region of interest retrieval of metallographic images for quality classification in industry Automated region of interest retrieval of metallographic images for quality classification in industry
skos:notation
RIV/61989100:27740/12:86084961!RIV13-MPO-27740___
n12:predkladatel
n17:orjk%3A27740
n3:aktivita
n18:P
n3:aktivity
P(FR-TI1/432)
n3:cisloPeriodika
1
n3:dodaniDat
n11:2013
n3:domaciTvurceVysledku
n4:3044521 n4:9411577
n3:druhVysledku
n16:J
n3:duvernostUdaju
n14:S
n3:entitaPredkladatele
n6:predkladatel
n3:idSjednocenehoVysledku
124182
n3:idVysledku
RIV/61989100:27740/12:86084961
n3:jazykVysledku
n19:eng
n3:klicovaSlova
industry; classification; quality; for; images; metallographic; retrieval; interest; region; Automated
n3:klicoveSlovo
n7:images n7:region n7:metallographic n7:industry n7:classification n7:quality n7:for n7:interest n7:Automated n7:retrieval
n3:kodStatuVydavatele
SK - Slovenská republika
n3:kontrolniKodProRIV
[843E1981EE94]
n3:nazevZdroje
Advances in Electrical and Electronic Engineering
n3:obor
n8:BB
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
5
n3:projekt
n5:FR-TI1%2F432
n3:rokUplatneniVysledku
n11:2012
n3:svazekPeriodika
10
n3:tvurceVysledku
Vesna, Zeljkovic Vondrák, Vít Ladislav, Válek Praks, Pavel Kotas, Petr
s:issn
1336-1376
s:numberOfPages
7
n15:organizacniJednotka
27740