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Statements

Subject Item
n2:RIV%2F00216224%3A14330%2F14%3A00073550%21RIV15-MSM-14330___
rdf:type
n12:Vysledek skos:Concept
dcterms:description
In biomedical image analysis, object description and classification tasks are very common. Our work relates to the problem of classification of Human Epithelial (HEp-2) cells. Since the crucial part of each classification process is the feature extraction and selection, much attention should be concentrated to the development of proper image descriptors. In this article, we introduce a new efficient texture-based image descriptor for HEp-2 images. We compare proposed descriptor with LBP, Haralick features (GLCM statistics) and Tamura features using the public MIVIA HEp-2 Images Dataset. Our descriptor outperforms all previously mentioned approaches and the classifier based solely on the proposed descriptor is able to achieve the accuracy as high as 87.8%. In biomedical image analysis, object description and classification tasks are very common. Our work relates to the problem of classification of Human Epithelial (HEp-2) cells. Since the crucial part of each classification process is the feature extraction and selection, much attention should be concentrated to the development of proper image descriptors. In this article, we introduce a new efficient texture-based image descriptor for HEp-2 images. We compare proposed descriptor with LBP, Haralick features (GLCM statistics) and Tamura features using the public MIVIA HEp-2 Images Dataset. Our descriptor outperforms all previously mentioned approaches and the classifier based solely on the proposed descriptor is able to achieve the accuracy as high as 87.8%.
dcterms:title
RSurf - the Efficient Texture-Based Descriptor for Fluorescence Microscopy Images of HEp-2 Cells RSurf - the Efficient Texture-Based Descriptor for Fluorescence Microscopy Images of HEp-2 Cells
skos:prefLabel
RSurf - the Efficient Texture-Based Descriptor for Fluorescence Microscopy Images of HEp-2 Cells RSurf - the Efficient Texture-Based Descriptor for Fluorescence Microscopy Images of HEp-2 Cells
skos:notation
RIV/00216224:14330/14:00073550!RIV15-MSM-14330___
n3:aktivita
n13:S n13:P
n3:aktivity
P(GBP302/12/G157), S
n3:dodaniDat
n11:2015
n3:domaciTvurceVysledku
n9:6056229 n9:6909779 n9:3323188
n3:druhVysledku
n20:D
n3:duvernostUdaju
n7:S
n3:entitaPredkladatele
n4:predkladatel
n3:idSjednocenehoVysledku
43536
n3:idVysledku
RIV/00216224:14330/14:00073550
n3:jazykVysledku
n19:eng
n3:klicovaSlova
texture descriptor; rsurf; hep-2
n3:klicoveSlovo
n8:rsurf n8:texture%20descriptor n8:hep-2
n3:kontrolniKodProRIV
[8984A2F7556C]
n3:mistoKonaniAkce
Stockholm, Sweden
n3:mistoVydani
Los Alamitos, California
n3:nazevZdroje
22nd International Conference on Pattern Recognition
n3:obor
n6:JD
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
3
n3:projekt
n15:GBP302%2F12%2FG157
n3:rokUplatneniVysledku
n11:2014
n3:tvurceVysledku
Stoklasa, Roman Svoboda, David Majtner, Tomáš
n3:typAkce
n18:WRD
n3:zahajeniAkce
2014-01-01+01:00
s:issn
1051-4651
s:numberOfPages
6
n22:doi
10.1109/ICPR.2014.215
n14:hasPublisher
IEEE Computer Society
n21:isbn
9781479952083
n17:organizacniJednotka
14330