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|a DE-627
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|e rakwb
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|a eng
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|a Campisi, Patrizio
|e verfasserin
|4 aut
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|a Reduced complexity rotation invariant texture classification using a blind deconvolution approach
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|c 2006
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|a Text
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|a ohne Hilfsmittel zu benutzen
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|a Date Completed 01.02.2006
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|a Date Revised 10.12.2019
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|a published: Print
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|a Citation Status MEDLINE
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|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
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|a Evaluation Study
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|a Journal Article
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|a Colonnese, Stefania
|e verfasserin
|4 aut
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|a Panci, Gianpiero
|e verfasserin
|4 aut
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|a Scarano, Gaetano
|e verfasserin
|4 aut
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|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
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|g volume:28
|g year:2006
|g number:1
|g day:24
|g month:01
|g pages:145-9
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