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Local phase quantization descriptors for blur robust and illumination invariant recognition of color textures

机译:局部相位量化描述符,可对颜色纹理进行模糊鲁棒和光照不变识别

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A novel extension for color images of the local phase quantization (LPQ) local descriptor is presented. The descriptor is obtained by using a multivector representation of color values in order to derive blur-robust features in frequency domain. We tested the proposed descriptor in texture classification problems, and quantified its robustness for several amounts of blur. The experiments show that the proposed descriptor achieves superior accuracy over its grayscale counterpart and other color texture descriptors. Furthermore its illumination-invariance properties guarantee remarkable performances in challenging scenarios of varying illumination, without the need of preprocessing textures with color-constancy algorithms.
机译:提出了一种新颖的彩色图像局部相位量化(LPQ)局部描述符扩展。通过使用颜色值的多矢量表示获得描述符,以便在频域中得出模糊鲁棒特征。我们在纹理分类问题中测试了提出的描述符,并针对几种模糊量对其鲁棒性进行了量化。实验表明,提出的描述符比其灰度副本和其他颜色纹理描述符具有更高的精度。此外,它的照度不变特性确保了在变化的照度具有挑战性的场景下的出色性能,而无需使用颜色恒定算法对纹理进行预处理。

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