Texture classification became one of the problems which has been paid much
attention on by image processing scientists since late 80s. Consequently, since
now many different methods have been proposed to solve this problem. In most of
these methods the researchers attempted to describe and discriminate textures
based on linear and non-linear patterns. The linear and non-linear patterns on
any window are based on formation of Grain Components in a particular order.
Grain component is a primitive unit of morphology that most meaningful
information often appears in the form of occurrence of that. The approach which
is proposed in this paper could analyze the texture based on its grain
components and then by making grain components histogram and extracting
statistical features from that would classify the textures. Finally, to
increase the accuracy of classification, proposed approach is expanded to color
images to utilize the ability of approach in analyzing each RGB channels,
individually. Although, this approach is a general one and it could be used in
different applications, the method has been tested on the stone texture and the
results can prove the quality of approach.

这篇研究论文介绍了一种基于图像纹理的粒子元素的直方图和统计特征的分类方法，并对彩色图像进行了扩展，以利用该方法在分析每个 RGB 通道方面的能力。该方法被测试于石头纹理分类，其结果证明了该方法的质量。