Combining local binary patterns and local color contrast for texture classification under varying illumination
Combining local binary patterns and local color contrast for texture classification under varying illumination
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DOI：
10.1364/josaa.31.001453
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发表时间：
2014-07-01
影响因子：
1.9
通讯作者：
Schettini, Raimondo
中科院分区：
文献类型：
--
作者：
Cusano, Claudio;Napoletano, Paolo;Schettini, Raimondo
本文提出了一种用于颜色纹理分类的纹理描述符，专门设计用于对照明条件的变化具有鲁棒性。该描述符将局部二值模式 (LBP) 的直方图与测量局部颜色对比度分布的新颖特征相结合。所提出的描述符相对于图像平面的旋转和平移以及相对于颜色空间中的多种变换是不变的。我们通过测量在不同光源下获取训练和测试图像的情况下的分类准确性，在 Outex 测试套件上评估了所提出的描述符。获得的结果表明，我们的描述符优于原始 LBP 方法及其颜色变体，即使这些是在颜色归一化之后计算的。此外，它还优于现有技术中的其他几种颜色纹理描述符。 (C) 2014年美国光学学会
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. (C) 2014 Optical Society of America