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In computer vision, texture plays an important role. In this work we propose five human perceptual texture features heuristically extracted. Since a modeling can not be obtained from these features, we use a discriminant analysis technique to examine the discriminant power of each texture descriptor in order to select the most relevant. This task is done by a stepwise inclusion of variables indicating, furthermore, whether all of them are valuable and necessary producing a set of optimal discriminant variables. These selection procedures have been tested using Brodatz texture images, a benchmark in texture analysis.

Stepwise selection of perceptual texture features