  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.
