基于灰度共生矩阵的煤与矸石自动识别研究

Automatic coal-gangue identification based on gray level co-occurrence matrix

为提高煤与矸石识别率,提出了一种基于灰度共生矩阵的煤与矸石纹理特征自动识别方法。分析灰度共生矩阵的基本原理、特征参数,利用灰度共生矩阵提取煤与矸石图像的角二阶距、相关性、对比度和熵这四个特征作为纹理特征,用支持向量机进行识别,并在MATLAB上仿真实现。研究结果表明:用灰度共生矩阵提取纹理特征、用支持向量机识别的方法能有效的描述煤与矸石的纹理特征,为煤与矸石的识别和分选提供重要参考依据。

To improve the coal- gangue identification rate,an automatic identification method of coal and gangue texture feature is proposed based on gray level co- occurrence matrix（ GLCM）. The basic principle of the GLCM,characteristic parameters are analyzed,and GLCM is utilized to extract texture features of coal and gangue image,including angular second moment, correlation, contrast and entropy, which are identified using support vector machine（ SVM）. The method has been simulated with MATLAB, and the results show that, texture features extraction with GLCM, SVM recognition method can effectively describe the texture characteristics of coal and gangue.