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Directional Analysis of Texture Images Using Gray Level Co-Occurrence Matrix

机译:灰度共发生矩阵纹理图像的方向分析

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Direction parameter θ is one of the important parameters of GLCM (gray level co-occurrence matrix). A fixed angle (such as θ=45°) or the average of themeasurements in four direction (θ=0°,45°,90°,135°) were usually used in calculating GLCM. However, these methods are just empiristic idea, lacking of theoretical support. In fact, the above-mentioned idea are usually failed to describe the image texture, especially for those texture images with strong directional characteristics. In this paper we propose a new method of choosing the maindirection of texture image by calculating the correlation of GLCMs of different direction. Through selecting the texture characteristics value of main direction, combine with the average of the measurements in other three directions, a set of characteristics which includes more texture information and rotation invariance were extracted. The experiments on Brodatz and Outex texture database show that the characteristic set we selected is more discriminate and more accurate.
机译:方向参数θ是GLCM(灰度共存矩阵)的重要参数之一。在四方向(θ= 0°,45°,90°,90°,135°,135°,135°)通常使用固定角度(例如θ= 45°)或平均水平的平均值。然而,这些方法只是凭证的想法,缺乏理论支持。事实上,上述思想通常未能描述图像纹理,特别是对于具有强向定向特性的纹理图像。在本文中,我们提出了一种通过计算不同方向的GLCM的相关性来选择纹理图像的主导的方法。通过选择主方向的纹理特性值,与其他三个方向的测量的平均值相结合,提取包括更多纹理信息和旋转不变性的一组特征。 Brodatz和Outex纹理数据库的实验表明,我们选择的特征集更为区分,更准确。

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