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Statements

Subject Item
n2:RIV%2F67985556%3A_____%2F08%3A00317589%21RIV10-MSM-67985556
rdf:type
skos:Concept n21:Vysledek
dcterms:description
We propose textural features, which are invariant to illumination spectrum and extremely robust to illumination direction. They require only a single training image per texture and no knowledge of illumination direction or spectrum. Hence, these features are suitable for content-based image retrieval (CBIR) of realistic scenes with colour textured objects and variable illumination. The illumination invariants are derived from Markov random field based texture representations. Our illumination invariant features are favourably compared with frequented features in this area - the Local Binary Patterns, steerable pyramid and Gabor textural features, respectively. The superiority of our new invariant features is demonstrated in the illumination invariant recognition of the most advanced representation for realistic real-world materiále - Bidirectional Texture Function (BTF) textures. We propose textural features, which are invariant to illumination spectrum and extremely robust to illumination direction. They require only a single training image per texture and no knowledge of illumination direction or spectrum. Hence, these features are suitable for content-based image retrieval (CBIR) of realistic scenes with colour textured objects and variable illumination. The illumination invariants are derived from Markov random field based texture representations. Our illumination invariant features are favourably compared with frequented features in this area - the Local Binary Patterns, steerable pyramid and Gabor textural features, respectively. The superiority of our new invariant features is demonstrated in the illumination invariant recognition of the most advanced representation for realistic real-world materiále - Bidirectional Texture Function (BTF) textures.
dcterms:title
Illumination Invariants Based on Markov Random Fields Illumination Invariants Based on Markov Random Fields
skos:prefLabel
Illumination Invariants Based on Markov Random Fields Illumination Invariants Based on Markov Random Fields
skos:notation
RIV/67985556:_____/08:00317589!RIV10-MSM-67985556
n3:aktivita
n7:P n7:Z
n3:aktivity
P(1ET400750407), P(1M0572), P(2C06019), P(GA102/08/0593), Z(AV0Z10750506)
n3:dodaniDat
n6:2010
n3:domaciTvurceVysledku
n8:1555170 n8:2890542
n3:druhVysledku
n10:D
n3:duvernostUdaju
n19:S
n3:entitaPredkladatele
n17:predkladatel
n3:idSjednocenehoVysledku
371390
n3:idVysledku
RIV/67985556:_____/08:00317589
n3:jazykVysledku
n12:eng
n3:klicovaSlova
illumination invariants; Markov random fields; texture
n3:klicoveSlovo
n4:illumination%20invariants n4:Markov%20random%20fields n4:texture
n3:kontrolniKodProRIV
[B2FF6CE30179]
n3:mistoKonaniAkce
Tampa
n3:mistoVydani
Los Alamitos
n3:nazevZdroje
Proceedings of the 19th International Conference on Pattern Recognition
n3:obor
n18:BD
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n5:1ET400750407 n5:2C06019 n5:GA102%2F08%2F0593 n5:1M0572
n3:rokUplatneniVysledku
n6:2008
n3:tvurceVysledku
Vácha, Pavel Haindl, Michal
n3:typAkce
n11:WRD
n3:zahajeniAkce
2008-12-07+01:00
n3:zamer
n16:AV0Z10750506
s:numberOfPages
4
n20:hasPublisher
IEEE Press
n15:isbn
978-1-4244-2174-9