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结合局部二值模式和局部颜色对比度用于不同光照下的纹理分类。

Combining local binary patterns and local color contrast for texture classification under varying illumination.

作者信息

Cusano Claudio, Napoletano Paolo, Schettini Raimondo

出版信息

J Opt Soc Am A Opt Image Sci Vis. 2014 Jul 1;31(7):1453-61. doi: 10.1364/JOSAA.31.001453.

Abstract

This paper presents a texture descriptor for color texture classification specially designed to be robust against changes in the illumination conditions. The descriptor combines a histogram of local binary patterns (LBPs) with a novel feature measuring the distribution of local color contrast. The proposed descriptor is invariant with respect to rotations and translations of the image plane and with respect to several transformations in the color space. We evaluated the proposed descriptor on the Outex test suite, by measuring the classification accuracy in the case in which training and test images have been acquired under different illuminants. The results obtained show that our descriptor outperforms the original LBP approach and its color variants, even when these are computed after color normalization. Moreover, it also outperforms several other color texture descriptors in the state of the art.

摘要

本文提出了一种用于颜色纹理分类的纹理描述符,该描述符经过专门设计,能够有效抵御光照条件变化的影响。该描述符将局部二值模式(LBP)直方图与一种用于测量局部颜色对比度分布的新特征相结合。所提出的描述符对于图像平面的旋转和平移以及颜色空间中的多种变换具有不变性。我们通过测量在不同光源下获取训练图像和测试图像时的分类准确率,在Outex测试套件上对所提出的描述符进行了评估。所得结果表明,即使在颜色归一化后计算,我们的描述符也优于原始的LBP方法及其颜色变体。此外,它还优于当前技术水平下的其他几种颜色纹理描述符。

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