Conference Papers Year : 2016

A new LBP histogram selection score for color texture classification

Abstract

This paper presents and compares a new adapted version of the Laplacian score used to select LBP histogram for color texture classification. During a supervised learning stage, we first compute a similarity matrix between images using the true class labels of these images. Then, a score is attributed to each histogram. This score allows to measure the capability of the histogram of preserving the similarity matrix. The histograms are then ranked according to the proposed score and the most discriminant ones are selected. Experiments are achieved on benchmark color texture image databases in order to show the interest of the proposed score for histogram selection.

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Dates and versions

hal-03031129 , version 1 (30-11-2020)

Identifiers

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Mariam Kalakech, Alice Porebski, Nicolas Vandenbroucke, Denis Hamad. A new LBP histogram selection score for color texture classification. 2015 International Conference on Image Processing Theory, Tools and Applications (IPTA), Nov 2015, Orleans, France. pp.242-247, ⟨10.1109/IPTA.2015.7367138⟩. ⟨hal-03031129⟩
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