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231224s1986 xx ||||| 00| ||eng c |
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|a (DE-627)NLM21101589X
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|a (NLM)21869331
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|e rakwb
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|a eng
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|a Unser, M
|e verfasserin
|4 aut
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|a Sum and difference histograms for texture classification
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|c 1986
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|a Text
|b txt
|2 rdacontent
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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|a Band
|b nc
|2 rdacarrier
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|a Date Completed 02.10.2012
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|a Date Revised 12.11.2019
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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|a The sum and difference of two random variables with same variances are decorrelated and define the principal axes of their associated joint probability function. Therefore, sum and difference histograms are introduced as an alternative to the usual co-occurrence matrices used for texture analysis. Two maximum likelihood texture classifiers are presented depending on the type of object used for texture characterization (sum and difference histograms or some associated global measures). Experimental results indicate that sum and difference histograms used conjointly are nearly as powerful as cooccurrence matrices for texture discrimination. The advantage of the proposed texture analysis method over the conventional spatial gray level dependence method is the decrease in computation time and memory storage
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|a Journal Article
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|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 8(1986), 1 vom: 01. Jan., Seite 118-25
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnns
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|g year:1986
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|g day:01
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|g pages:118-25
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|d 8
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|h 118-25
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