Reduced complexity rotation invariant texture classification using a blind deconvolution approach

In this paper, we present a texture classification procedure that makes use of a blind deconvolution approach. Specifically, the texture is modeled as the output of a linear system driven by a binary excitation. We show that features computed from one-dimensional slices extracted from the two-dimens...

Description complète

Détails bibliographiques
Publié dans:IEEE transactions on pattern analysis and machine intelligence. - 1998. - 28(2006), 1 vom: 24. Jan., Seite 145-9
Auteur principal: Campisi, Patrizio (Auteur)
Autres auteurs: Colonnese, Stefania, Panci, Gianpiero, Scarano, Gaetano
Format: Article
Langue:English
Publié: 2006
Accès à la collection:IEEE transactions on pattern analysis and machine intelligence
Sujets:Evaluation Study Journal Article
LEADER 01000caa a22002652 4500
001 NLM160011167
003 DE-627
005 20250207003533.0
007 tu
008 231223s2006 xx ||||| 00| ||eng c
028 5 2 |a pubmed25n0533.xml 
035 |a (DE-627)NLM160011167 
035 |a (NLM)16402627 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Campisi, Patrizio  |e verfasserin  |4 aut 
245 1 0 |a Reduced complexity rotation invariant texture classification using a blind deconvolution approach 
264 1 |c 2006 
336 |a Text  |b txt  |2 rdacontent 
337 |a ohne Hilfsmittel zu benutzen  |b n  |2 rdamedia 
338 |a Band  |b nc  |2 rdacarrier 
500 |a Date Completed 01.02.2006 
500 |a Date Revised 10.12.2019 
500 |a published: Print 
500 |a Citation Status MEDLINE 
520 |a In this paper, we present a texture classification procedure that makes use of a blind deconvolution approach. Specifically, the texture is modeled as the output of a linear system driven by a binary excitation. We show that features computed from one-dimensional slices extracted from the two-dimensional autocorrelation function (ACF) of the binary excitation allows representing the texture for rotation-invariant classification purposes. The two-dimensional classification problem is thus reconduced to a more simple one-dimensional one, which leads to a significant reduction of the classification procedure computational complexity 
650 4 |a Evaluation Study 
650 4 |a Journal Article 
700 1 |a Colonnese, Stefania  |e verfasserin  |4 aut 
700 1 |a Panci, Gianpiero  |e verfasserin  |4 aut 
700 1 |a Scarano, Gaetano  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on pattern analysis and machine intelligence  |d 1998  |g 28(2006), 1 vom: 24. Jan., Seite 145-9  |w (DE-627)NLM098212257  |x 0162-8828  |7 nnns 
773 1 8 |g volume:28  |g year:2006  |g number:1  |g day:24  |g month:01  |g pages:145-9 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 28  |j 2006  |e 1  |b 24  |c 01  |h 145-9