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Texture classification using a new version of local binary patterns

机译:使用新版本的本地二进制模式进行纹理分类

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摘要

Among various feature extraction methods for texture classification, Local Binary Patterns and Modified Local Binary Patterns, because of simplicity and classification accuracy, have emerged as one of the most popular ones. LBP has simple implementation, but with increasing the radius of neighborhood, computational complexity will be increased. MLBP cannot classify non uniform textures as well as uniform ones. In this paper a new version of LBP is developed that has less computational complexity than LBP and more classification accuracy than MLBP. The proposed method classifies non uniform textures as well as uniform ones. Classification accuracy on two standard datasets, Brodatz and Outex, indicates efficiency of the proposed approach.
机译:在用于纹理分类的各种特征提取方法中,由于简单性和分类精度,局部二值模式和修改后的局部二值模式已成为最受欢迎的方法之一。 LBP具有简单的实现,但是随着邻域半径的​​增加,计算复杂度将增加。 MLBP无法对非均匀纹理和均匀纹理进行分类。在本文中,开发了新版本的LBP,它的计算复杂度低于LBP,分类精度高于MLBP。所提出的方法对非均匀纹理和均匀纹理进行了分类。两个标准数据集Brodatz和Outex的分类准确性表明了该方法的效率。

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