基于图像纹理的煤岩识别研究

Study on Coal and Rock Identification Based on Image Texture

煤岩识别对实现采掘面无人开采具有重要的意义。由于煤、岩石在纹理上的巨大差别,提出了基于图像纹理的煤岩识别研究。利用灰度共生矩阵(GLCM)分别对煤、岩石图像纹理进行特征提取,然后再应用RBF神经网络分析处理所得到的纹理特征数据,进而实现对煤岩的分类识别,通过验证,该方法准确率高,操作简单,值得推广。

Coal and rock identification is of great significance to the realization of unmanned mining surace mining. Becuase of the great difference in the texture on the coal and rock, put forward the research of coal and rock identification based on image texture. Using gray level co-occurrence matrix(GLCM) respectively for feature extraction of coal and rock texture. Then apply RBF neural network analysis and process the obtained texture datas, and then realize the identification of coal and rock,through the verification, the method is high accuracy, simple operation, worthy of promotion.