基于灰度共生矩阵的图像纹理特征提取分析

图像纹理作为一种重要的视觉手段，是图像中普遍存在而又难以描述的特征。目前常用的纹理特征提取的方法主要有统计方法、模型方法、信号处理方法和结构方法。灰度共生矩阵即为灰度级的空间相关矩阵，以其为基础的统计方法通过对矩阵统计量的求取较好地提取到了纹理特征，通过选取关键参数编程并进行仿真实现，分别求取了四个方向的灰度共生矩阵及其特征量来分析图像的纹理特征。

Analysis of GLCM Based Image Textural Features Extraction

As an important means of visual sense, image texture is of a feature which generally exists in images and is inenarrable. The usual methods of textural features extraction include statistical techniques, model chemistries, signal processing methods, and structural approaches. The Space intensity-based correlation matrix named Gray Level Co-occurrence Matrix, with its based statistical method could well extract the textural feature by means of getting the matrix statistic. By selecting the key parameters for programming and achieving the simulation, the GLCM and their characteristic quantities at different four directions are respectively gotten to analyze textural features of image.