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Rotation and Gray-Scale Invariant Classification of Textures Improved by Spatial Distribution of Features

机译:通过空间分布的特征旋转和灰度不变分类改善的纹理

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In this paper, we present a framework for texture descriptors based on spatial distribution of textural features. Our approach is based on the observation that regional properties of textures are well captured by correlations among local texture patterns. The proposed method has been evaluated through experiments using real textures, and has shown significant improvements in recognition rates.
机译:在本文中,我们为基于纹理特征的空间分布提供了一个纹理描述符的框架。我们的方法是基于观察结果,局部纹理模式之间的相关性拍摄纹理的区域性质。已经通过使用真实纹理的实验评估了该方法,并显示了识别率的显着改善。

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