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Title of Journal: Pattern Anal Applic

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Abbravation: Pattern Analysis and Applications

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Springer-Verlag

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10.1002/actp.1988.010390510

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1433-755X

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Supervised texture classification color space or

Authors: A Porebski N Vandenbroucke L Macaire
Publish Date: 2012/08/24
Volume: 16, Issue: 1, Pages: 1-18
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Abstract

The color of pixels can be represented in different color spaces which take into account different properties However no color space is wellsuited to the discrimination of all texture databases and the prior determination of such a space is not easy In this paper we compare the performances reached by two texture classification schemes that use color spaces a the single color space selection approach that defines a set of texture features and then selects the color space with which the texture features allow to reach the highest classification accuracy b the multicolor space feature selection MCSFS approach that selects texture features which have been processed from images coded into different color spaces Experiments carried out with benchmark texture databases show that taking advantage simultaneously of the properties of several color spaces thanks to the MCSFS approach improves the rates of wellclassified images with lower learning and decision processing times


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