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Texture Segmentation and Matching Using LBP Operator and GLCM Matrix

机译:使用LBP运算符和GLCM矩阵的纹理分割和匹配

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Image processing is a dynamic research area. Recently, a lot of works have been made, efficient approaches have been developed and good results have been obtained. In this work, we propose a new texture matching and segmenting approach based on a new decomposing architecture. This method starts with one main window MW. For each iteration, the MW is reduced and all possible windows with the same size of the MW are generated. The Local Binary Pattern LBP operator, which is gray-scale invariant texture measure, and the Gray Level Cooccurrence Matrix (GLCM), which is a second order statistics measure, have been applied independently to extract the features from each generated window. Synthetic images and test images generated randomly from Brodatz album have been used in the experimentation. Good performances have been obtained and some results will be shown in the test section of this chapter.
机译:图像处理是一个动态研究区域。最近,已经进行了许多作品,已经开发了有效的方法,并获得了良好的结果。在这项工作中,我们提出了一种基于新的分解架构的新纹理匹配和分段方法。此方法从一个主窗口MW开始。对于每次迭代,MW减少,并且产生了具有相同MW大小的所有可能的窗口。本地二进制模式LBP操作员是灰度不变纹理测量和灰度Cooccurrence矩阵(GLCM),它是二阶统计测量的措施,已独立应用,以从每个生成的窗口中提取该功能。从Brodatz专辑随机生成的合成图像和测试图像已在实验中使用。已经获得了良好的表现,并将在本章的测试部分中显示一些结果。

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